Search results for: production scheduling optimization

Authors: A. Sri Janani, K. Immanuel Arokia James

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Cognitive radio ad hoc networks different unlicensed users may acquire different available channel sets. This non-uniform spectrum availability imposes special design challenges for broadcasting in CR ad hoc networks. Cognitive radio automatically detects available channels in wireless spectrum. This is a form of dynamic spectrum management. Cross-layer optimization is proposed, using this can allow far away secondary users can also involve into channel work. So it can increase the throughput and it will overcome the collision and time delay.

Keywords: cognitive radio, cross layer optimization, CR mesh network, heterogeneous spectrum, mesh topology, random routing optimization technique

Procedia PDF Downloads 348

Authors: Abdulbaset Saad, Adel Younis, Zuomin Dong

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For design optimization with high-dimensional expensive problems, an effective and efficient optimization methodology is desired. This work proposes a series of modification to the Differential Evolution (DE) algorithm for solving computation Intensive Black-Box Problems. The proposed methodology is called Radial Basis Meta-Model Algorithm Assisted Differential Evolutionary (RBF-DE), which is a global optimization algorithm based on the meta-modeling techniques. A meta-modeling assisted DE is proposed to solve computationally expensive optimization problems. The Radial Basis Function (RBF) model is used as a surrogate model to approximate the expensive objective function, while DE employs a mechanism to dynamically select the best performing combination of parameters such as differential rate, cross over probability, and population size. The proposed algorithm is tested on benchmark functions and real life practical applications and problems. The test results demonstrate that the proposed algorithm is promising and performs well compared to other optimization algorithms. The proposed algorithm is capable of converging to acceptable and good solutions in terms of accuracy, number of evaluations, and time needed to converge.

Keywords: differential evolution, engineering design, expensive computations, meta-modeling, radial basis function, optimization

Procedia PDF Downloads 382

Authors: Linda D. F. Bambara, Marie Sawadogo

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Jatropha curcas (jatropha) is the plant that has been the most studied for biofuel production in West Africa. There exist however other plants such as Balanites aegyptiaca (balanites) that have been targeted as a potential feedstock for biofuel production. This biomass could be an alternative feedstock for the production of straight vegetable oil (SVO) at costs lower than jatropha-based SVO production costs. This study aims firstly to determine, through an MILP model, the optimal organization that minimizes the costs of the oilseeds supply of two biomass conversion units (BCU) exploiting respectively jatropha seeds and the balanitès seeds. Secondly, the study aims to carry out a comparative study of these costs obtained for each BCU. The model was then implemented on two theoretical cases studies built on the basis of the common practices in Burkina Faso and two scenarios were carried out for each case study. In Scenario 1, 3 pre-processing locations ("at the harvesting area", "at the gathering points", "at the BCU") are possible. In scenario 2, only one location ("at the BCU") is possible. For each biomass, the system studied is the upstream supply chain (harvesting, transport and pre-processing (drying, dehulling, depulping)), including cultivation (for jatropha). The model optimizes the area of land to be exploited based on the productivity of the studied plants and material losses that may occur during the harvesting and the supply of the BCU. It then defines the configuration of the logistics network allowing an optimal supply of the BCU taking into account the most common means of transport in West African rural areas. For the two scenarios, the results of the implementation showed that the total area exploited for balanites (1807 ha) is 4.7 times greater than the total area exploited for Jatropha (381 ha). In both case studies, the location of pre-processing “at the harvesting area” was always chosen for scenario1. As the balanites trees were not planted and because the first harvest of the jatropha seeds took place 4 years after planting, the cost price of the seeds at the BCU without the pre-processing costs was about 430 XOF/kg. This cost is 3 times higher than the balanites's one, which is 140 XOF/kg. After the first year of harvest, i.e. 5 years after planting, and assuming that the yield remains constant, the same cost price is about 200 XOF/kg for Jatropha. This cost is still 1.4 times greater than the balanites's one. The transport cost of the balanites seeds is about 120 XOF/kg. This cost is similar for the jatropha seeds. However, when the pre-processing is located at the BCU, i.e. for scenario2, the transport costs of the balanites seeds is 1200 XOF/kg. These costs are 6 times greater than the transport costs of jatropha which is 200 XOF/kg. These results show that the cost price of the balanites seeds at the BCU can be competitive compared to the jatropha's one if the pre-processing is located at the harvesting area.

Keywords: Balanites aegyptiaca, biomass conversion, Jatropha curcas, optimization, post-harvest operations

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Authors: N. Zerzouri, N. Benalia, N. Bensiali

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During recent years wind turbine technology has undergone rapid developments. Growth in size and the optimization of wind turbines has enabled wind energy to become increasingly competitive with conventional energy sources. As a result today’s wind turbines participate actively in the power production of several countries around the world. These developments raise a number of challenges to be dealt with now and in the future. The penetration of wind energy in the grid raises questions about the compatibility of the wind turbine power production with the grid. In particular, the contribution to grid stability, power quality and behavior during fault situations plays therefore as important a role as the reliability. In the present work, we addressed two fault situations that have shown their influence on the generator and the behavior of the wind over the defects which are briefly discussed based on simulation results.

Keywords: doubly fed induction generator (DFIG), wind energy, grid fault, electrical engineering

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Authors: Piyakajornkul T., Noppiboon S., Hochareon L., Kitsubun P.

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Nowadays, DNA vaccines become an interesting subject in the third vaccine generation. The platform of DNA vaccines production has been developed and its downstream process becomes challenging due to the quality of the products in terms of purity and percentage of supercoiled DNA. To overcome these challenges, tangential flow filtration (TFF), which is involved in the purification process, could be used since it provides effective separation of impurity prior to performing further purification steps. However, operating conditions of TFF is varied based on several factors such as sizes of target particle and impurities, a concentration of solution as well as a concentration polarization on the membrane surface. In this study, pVAX1/lacZ was used as a model of TFF optimization in order to prevent a concentration polarization that can lead to the membrane fouling and also minimize a diafiltration volume while maintaining the maximum permeate flux resulting in proper operating times and buffer volume. By using trans membrane pressure (TMP) excursion method, feed flow rates and TMP were varied. The results showed a correlation of permeate flux with TMP where the maximum volume concentration factor reached 2.5 times of the initial volume when feed flow rate and TMP were 7 liters/m²/min and 1 bar, respectively. It was optimal operating conditions before TFF system undergone pressure independent regime. In addition, the diafiltration volume was 14 times of the concentrated volume prior to performing a further anion chromatography process.

Keywords: concentration polarization, DNA vaccines, optimization, permeate flux, pressure dependent, tangential flow filtration (TFF), trans membrane pressure (TMP)

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Authors: Abbas Al-Refaie

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This paper aims at improving the performance of the tableting process using statistical quality control and fuzzy goal programming. The tableting process was studied. Statistical control tools were used to characterize the existing process for three critical responses including the averages of a tablet’s weight, hardness, and thickness. At initial process factor settings, the estimated process capability index values for the tablet’s averages of weight, hardness, and thickness were 0.58, 3.36, and 0.88, respectively. The L₉ array was utilized to provide experimentation design. Fuzzy goal programming was then employed to find the combination of optimal factor settings. Optimization results showed that the process capability index values for a tablet’s averages of weight, hardness, and thickness were improved to 1.03, 4.42, and 1.42, respectively. Such improvements resulted in significant savings in quality and production costs.

Keywords: fuzzy goal programming, control charts, process capability, tablet optimization

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Authors: Kuen Ming Shu, Ren Kai Ho

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Ultrasonic horn has the functions of amplifying amplitude and reducing resonant impedance in ultrasonic system. Its primary function is to amplify deformation or velocity during vibration and focus ultrasonic energy on the small area. It is a crucial component in design of ultrasonic vibration system. There are five common design methods for ultrasonic horns: analytical method, equivalent circuit method, equal mechanical impedance, transfer matrix method, finite element method. In addition, the general optimization design process is to change the geometric parameters to improve a single performance. Therefore, in the general optimization design process, we couldn't find the relation of parameter and objective. However, a good optimization design must be able to establish the relationship between input parameters and output parameters so that the designer can choose between parameters according to different performance objectives and obtain the results of the optimization design. In this study, an ultrasonic horn provided by Maxwide Ultrasonic co., Ltd. was used as the contrast of optimized ultrasonic horn. The ANSYS finite element analysis (FEA) software was used to simulate the distribution of the horn amplitudes and the natural frequency value. The results showed that the frequency for the simulation values and actual measurement values were similar, verifying the accuracy of the simulation values. The ANSYS DesignXplorer was used to perform Response Surface optimization, which could shows the relation of parameter and objective. Therefore, this method can be used to substitute the traditional experience method or the trial-and-error method for design to reduce material costs and design cycles.

Keywords: horn, natural frequency, response surface optimization, ultrasonic vibration

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Authors: C. Andreu Sabater, D. Drago, C. Key-aberg, W. Moukrim, B. Naccache

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Present study concerns the optimization of a new vertical axis wind turbine system associated to a dynamoelectric motor. The system is composed by three Savonius wind turbines, arranged in an equilateral triangle. The idea is to propose a new concept of wind turbines through a technical approach allowing find a specific power never obtained before and therefore, a significant reduction of installation costs. In this work different wind flows across the system have been simulated, as well as precise definition of parameters and relations established between them. It will allow define the optimal rotor specific power for a given volume. Calculations have been developed with classical Savonius dimensions.

Keywords: VAWT, savonius, specific power, optimization, weibull

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Authors: Rony Tawk, Boutros Ghannam, Maroun Nemer

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Topology optimization technique presents a potential tool for the design and optimization of structures involved in mass and heat transfer. The method starts with an initial intermediate domain and should be able to progressively distribute the solid and the two fluids exchanging heat. The multi-objective function of the problem takes into account minimization of total pressure loss and maximization of heat transfer between solid and fluid subdomains. Existing methods account for the presence of only one fluid, while the actual work extends optimization distribution of solid and two different fluids. This requires to separate the channels of both fluids and to ensure a minimum solid thickness between them. This is done by adding a third objective function to the multi-objective optimization problem. This article uses density approach where each cell holds two local design parameters ranging from 0 to 1, where the combination of their extremums defines the presence of solid, cold fluid or hot fluid in this cell. Finite volume method is used for direct solver coupled with a discrete adjoint approach for sensitivity analysis and method of moving asymptotes for numerical optimization. Several examples are presented to show the ability of the method to find a trade-off between minimization of power dissipation and maximization of heat transfer while ensuring the separation and continuity of the channel of each fluid without crossing or mixing the fluids. The main conclusion is the possibility to find an optimal bi-fluid domain using topology optimization, defining a fluid to fluid heat exchanger device.

Keywords: topology optimization, density approach, bi-fluid domain, laminar steady state regime, fluid-to-fluid heat exchanger

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Authors: Elham Kiyani

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In this paper, we first introduce the concept of Q-efficient solutions in a real linear space not necessarily endowed with a topology, where Q is some nonempty (not necessarily convex) set. We also used the scalarization technique including the Gerstewitz function generated by a nonconvex set to characterize these Q-efficient solutions. The algebraic concepts of interior and closure are useful to study optimization problems without topology. Studying nonconvex vector optimization is valuable since topological interior is equal to algebraic interior for a convex cone. So, we use the algebraic concepts of interior and closure to define Q-weak efficient solutions and Q-Henig proper efficient solutions of set-valued optimization problems, where Q is not a convex cone. Optimization problems with set-valued maps have a wide range of applications, so it is expected that there will be a useful analytical tool in optimization theory for set-valued maps. These kind of optimization problems are closely related to stochastic programming, control theory, and economic theory. The paper focus on nonconvex problems, the results are obtained by assuming generalized non-convexity assumptions on the data of the problem. In convex problems, main mathematical tools are convex separation theorems, alternative theorems, and algebraic counterparts of some usual topological concepts, while in nonconvex problems, we need a nonconvex separation function. Thus, we consider the Gerstewitz function generated by a general set in a real linear space and re-examine its properties in the more general setting. A useful approach for solving a vector problem is to reduce it to a scalar problem. In general, scalarization means the replacement of a vector optimization problem by a suitable scalar problem which tends to be an optimization problem with a real valued objective function. The Gerstewitz function is well known and widely used in optimization as the basis of the scalarization. The essential properties of the Gerstewitz function, which are well known in the topological framework, are studied by using algebraic counterparts rather than the topological concepts of interior and closure. Therefore, properties of the Gerstewitz function, when it takes values just in a real linear space are studied, and we use it to characterize Q-efficient solutions of vector problems whose image space is not endowed with any particular topology. Therefore, we deal with a constrained vector optimization problem in a real linear space without assuming any topology, and also Q-weak efficient and Q-proper efficient solutions in the senses of Henig are defined. Moreover, by means of the Gerstewitz function, we provide some necessary and sufficient optimality conditions for set-valued vector optimization problems.

Keywords: algebraic interior, Gerstewitz function, vector closure, vector optimization

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Authors: Wlodzimierz Ogryczak, Michal Przyluski, Tomasz Sliwinski

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In problems of portfolio selection, the reward-risk ratio criterion is optimized to search for a risky portfolio with the maximum increase of the mean return in proportion to the risk measure increase when compared to the risk-free investments. In the classical model, following Markowitz, the risk is measured by the variance thus representing the Sharpe ratio optimization and leading to the quadratic optimization problems. Several Linear Programming (LP) computable risk measures have been introduced and applied in portfolio optimization. In particular, the Mean Absolute Deviation (MAD) measure has been widely recognized. The reward-risk ratio optimization with the MAD measure can be transformed into the LP formulation with the number of constraints proportional to the number of scenarios and the number of variables proportional to the total of the number of scenarios and the number of instruments. This may lead to the LP models with huge number of variables and constraints in the case of real-life financial decisions based on several thousands scenarios, thus decreasing their computational efficiency and making them hardly solvable by general LP tools. We show that the computational efficiency can be then dramatically improved by an alternative model based on the inverse risk-reward ratio minimization and by taking advantages of the LP duality. In the introduced LP model the number of structural constraints is proportional to the number of instruments thus not affecting seriously the simplex method efficiency by the number of scenarios and therefore guaranteeing easy solvability. Moreover, we show that under natural restriction on the target value the MAD risk-reward ratio optimization is consistent with the second order stochastic dominance rules.

Keywords: portfolio optimization, reward-risk ratio, mean absolute deviation, linear programming

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Authors: Vasilios Kanellopoulos

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The present paper examines the effect of innovation efficiency on the production of new knowledge from a firm level perspective. It resorts to the Greek version of community innovation survey (CIS 2012-2014 microdata) and employs 1274 firms of the manufacturing, which constitutes the main sector of examination. It assumes a knowledge production function (KPF) and finds that R&D spillovers related to the expenditures on innovation activities, internal R&D, external R&D, skilled labor, and the expenditures in the acquisition of machinery have a positive and significant effect on the production of new knowledge when OLS techniques are applied. However, innovation efficiency comes from a Banker and Morey (1986) data envelopment analysis (DEA) with categorical variables has a statistically insignificant impact on the production of new knowledge measured by firm’s turnover.

Keywords: firms, innovation efficiency, production of new knowledge, R&D spillovers

Procedia PDF Downloads 124

Authors: Egemen Sert, Leila Hedayatifar, Rachel A. Rigg, Amir Akhavan, Olha Buchel, Dominic Elias Saadi, Aabir Abubaker Kar, Alfredo J. Morales, Yaneer Bar-Yam

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The complexity of providing timely and cost-effective distribution of finished goods from industrial facilities to customers makes effective operational coordination difficult, yet effectiveness is crucial for maintaining customer service levels and sustaining a business. Logistics planning becomes increasingly complex with growing numbers of customers, varied geographical locations, the uncertainty of future orders, and sometimes extreme competitive pressure to reduce inventory costs. Linear optimization methods become cumbersome or intractable due to a large number of variables and nonlinear dependencies involved. Here we develop a complex systems approach to optimizing logistics networks based upon dimensional reduction methods and apply our approach to a case study of a manufacturing company. In order to characterize the complexity in customer behavior, we define a “customer space” in which individual customer behavior is described by only the two most relevant dimensions: the distance to production facilities over current transportation routes and the customer's demand frequency. These dimensions provide essential insight into the domain of effective strategies for customers; direct and indirect strategies. In the direct strategy, goods are sent to the customer directly from a production facility using box or bulk trucks. In the indirect strategy, in advance of an order by the customer, goods are shipped to an external warehouse near a customer using trains and then "last-mile" shipped by trucks when orders are placed. Each strategy applies to an area of the customer space with an indeterminate boundary between them. Specific company policies determine the location of the boundary generally. We then identify the optimal delivery strategy for each customer by constructing a detailed model of costs of transportation and temporary storage in a set of specified external warehouses. Customer spaces help give an aggregate view of customer behaviors and characteristics. They allow policymakers to compare customers and develop strategies based on the aggregate behavior of the system as a whole. In addition to optimization over existing facilities, using customer logistics and the k-means algorithm, we propose additional warehouse locations. We apply these methods to a medium-sized American manufacturing company with a particular logistics network, consisting of multiple production facilities, external warehouses, and customers along with three types of shipment methods (box truck, bulk truck and train). For the case study, our method forecasts 10.5% savings on yearly transportation costs and an additional 4.6% savings with three new warehouses.

Keywords: logistics network optimization, direct and indirect strategies, K-means algorithm, dimensional reduction

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Authors: Jason Digalakis, John Cotronis

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Memetic algorithms (MAs) are useful for solving optimization problems. It is quite difficult to search the search space of the optimization problem with large dimensions. There is a challenge to use all the cores of the system. In this study, a sequential implementation of the memetic algorithm is converted into a concurrent version, which is executed on the cores of both CPU and GPU. For this reason, CUDA and OpenMP libraries are operated on the parallel algorithm to make a concurrent execution on CPU and GPU, respectively. The aim of this study is to compare CPU and GPU implementation of the memetic algorithm. For this purpose, fourteen benchmark functions are selected as test problems. The obtained results indicate that our approach leads to speedups up to five thousand times higher compared to one CPU thread while maintaining a reasonable results quality. This clearly shows that GPUs have the potential to acceleration of MAs and allow them to solve much more complex tasks.

Keywords: memetic algorithm, CUDA, GPU-based memetic algorithm, open multi processing, multimodal functions, unimodal functions, non-linear optimization problems

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Authors: Xinhuang Wu, Yousef Sardahi

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A hybrid and optimal multi-loop control structure combining linear and nonlinear control algorithms are introduced in this paper to regulate the position of a quadcopter unmanned aerial vehicle (UAV) driven by four brushless DC motors. To this end, a nonlinear mathematical model of the UAV is derived and then linearized around one of its operating points. Using the nonlinear version of the model, a sliding mode control is used to derive the control laws of the motor thrust forces required to drive the UAV to a certain position. The linear model is used to design two controllers, XG-controller and YG-controller, responsible for calculating the required roll and pitch to maneuver the vehicle to the desired X and Y position. Three attitude controllers are designed to calculate the desired angular rates of rotors, assuming that the Euler angles are minimal. After that, a many-objective optimization problem involving 20 design parameters and ten objective functions is formulated and solved by HypE (Hypervolume estimation algorithm), one of the widely used many-objective optimization algorithms approaches. Both stability and performance constraints are imposed on the optimization problem. The optimization results in terms of Pareto sets and fronts are obtained and show that some of the design objectives are competing. That is, when one objective goes down, the other goes up. Also, Numerical simulations conducted on the nonlinear UAV model show that the proposed optimization method is quite effective.

Keywords: optimal control, many-objective optimization, sliding mode control, linear control, cascade controllers, UAV, drones

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Authors: Anurag Jain, Rajneesh Kumar

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Cloud computing is the outcome of rapid growth of internet. Due to elastic nature of cloud computing and unpredictable behavior of user, load balancing is the major issue in cloud computing paradigm. An efficient load balancing technique can improve the performance in terms of efficient resource utilization and higher customer satisfaction. Load balancing can be implemented through task scheduling, resource allocation and task migration. Various parameters to analyze the performance of load balancing approach are response time, cost, data processing time and throughput. This paper demonstrates a two level load balancer approach by combining join idle queue and join shortest queue approach. Authors have used cloud analyst simulator to test proposed two level load balancer approach. The results are analyzed and compared with the existing algorithms and as observed, proposed work is one step ahead of existing techniques.

Keywords: cloud analyst, cloud computing, join idle queue, join shortest queue, load balancing, task scheduling

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Authors: Van-Thanh Ho, Hyoungsoon Lee, Jaiyoung Ryu

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Efficient pressure distribution within soft robotic systems, specifically to the pneumatic artificial muscle (PAM) regions, is essential to minimize energy consumption. This optimization involves adjusting reservoir pressure, pipe diameter, and branching network layout to reduce flow speed and pressure drop while enhancing flow efficiency. The outcome of this optimization is a lightweight power source and reduced mechanical impedance, enabling extended wear and movement. To achieve this, a branching network system was created by combining pipe components and intricate cross-sectional area variations, employing the principle of minimal work based on a complete virtual human exosuit. The results indicate that modifying the cross-sectional area of the branching network, gradually decreasing it, reduces velocity and enhances momentum compensation, preventing flow disturbances at separation regions. These optimized designs achieve uniform velocity distribution (uniformity index > 94%) prior to entering the connection pipe, with a pressure drop of less than 5%. The design must also consider the length-to-diameter ratio for fluid dynamic performance and production cost. This approach can be utilized to create a comprehensive PAM system, integrating well-designed tube networks and complex pneumatic models.

Keywords: pneumatic artificial muscles, pipe networks, pressure drop, compressible turbulent flow, uniformity flow, murray's law

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Authors: Omar Bouhassoun, Cristian Garrido, César Hueso

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The radiation shielding design is an optimization problem with multiple -constrained- objective functions (radiation dose, weight, price, etc.) that depend on several parameters (material, thickness, position, etc.). The classical approach for shielding design consists of a brute force trial-and-error process subject to previous designer experience. Therefore, the result is an empirical solution but not optimal, which can degrade the overall performance of the shielding. In order to automate the shielding design procedure, the IDOM Shielding Optimization Tool (ISOT) has been developed. This software combines optimization algorithms with the capabilities to read/write input files, run calculations, as well as parse output files for different radiation transport codes. In the first stage, the software was established to adjust the input files for two well-known Monte Carlo codes (MCNP and Serpent) and optimize the result (weight, volume, price, dose rate) using multi-objective genetic algorithms. Nevertheless, its modular implementation easily allows the inclusion of more radiation transport codes and optimization algorithms. The work related to the development of ISOT and its verification on a simple 3D multi-layer shielding problem using both MCNP and Serpent will be presented. ISOT looks very promising for achieving an optimal solution to complex shielding problems.

Keywords: optimization, shielding, nuclear, genetic algorithm

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Authors: Rameesha Javaid

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Agriculture is the backbone of the economy of the province of Balochistan which is known as the ‘fruit basket’ of Pakistan. Its climate zones comprising highlands and plateaus, dependent on rain water, are more suited for the production of deciduous fruit. The vagaries of weather and more so the persistent droughts prompted the government to announce flat rates of electricity bills per month irrespective of the size of the farm, quantum or water used and the category of crop group. That has, no doubt, resulted in increased cropping intensity, more production and employment but has enormously burdened the official exchequer which picks up the residual bills in certain percentages amongst the federal and provincial governments and the local electricity company. This study tests the desirability of continuing the subsidy in the present mode. Optimization of social welfare of farmers has been the focus of the study with emphasis on the contribution of positive externalities and distortions caused in terms of negative externalities. By using the optimization technique with due allowance for distortions, it has been established that the subsidy calls for limiting policy distortions as they cause sub-optimal utilization of the tube well subsidy and improved policy programming. The sensitivity analysis with changed rankings of contributing variables towards social welfare does not significantly change the result. Therefore it leads to the net findings and policy recommendations of significantly reducing the subsidy size, correcting and curtailing policy distortions and targeting the subsidy grant more towards small farmers to generate more welfare by saving a sizeable amount from the subsidy for investment in the wellbeing of the farmers in rural Balochistan.

Keywords: distortion, policy distortion, socio-cultural distortion, social welfare, subsidy

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Authors: Zair Firdaous, Fourka Mohamed, Elfelsoufi Zoubir

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The arrival of e-commerce has changed the supply chain management on the operational level as well as on the organization and strategic and even tactical decisions of the companies. The optimization of resources is an issue that is needed on the tactical and operational strategic plan. This work considers the allocation of resources in the case of pure players that have launched online sales. The aim is to improve the level of customer satisfaction and maintaining the benefits of e-retailer and of its cooperators and reducing costs and risks. We first modeled the B2C chain with all operations that integrates and possible scenarios since online retailers offer a wide selection of personalized service. The personalized services that online shopping companies offer to the clients can be embodied in many aspects, such as the customizations of payment, the distribution methods, and after-sales service choices. Every aspect of customized service has several modes. At that time, we analyzed the optimization problems of supply chain resource in customized online shopping service mode. Then, we realized an optimization model and algorithm for the development based on the analysis of the of the B2C supply chain resources. It is a multi-objective optimization that considers the collaboration of resources in operations, time and costs but also the risks and the quality of services as well as dynamic and uncertain characters related to the request.

Keywords: supply chain resource, e-commerce, pure-players, optimization

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Authors: K. Suheiti, P. Soni, Yardha

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Challenges ahead of Indonesian agricultural development include increasing rural welfare, food needs, and the provision of employment through resource optimization that are laid out in agribusiness system. The agricultural system also responsive to the changing strategic environment. However, mounting pressure of population increase and changes in land-uses, require intensive use of agricultural land with modern agricultural machinery. Similarly, environmentally friendly technologies should continue to be developed in an effort to build and develop a good farming practice model. This paper explains the development of agricultural mechanization in Indonesia, particularly on rice production. The method of the research was analyze secondary data, tabulation and interpretation. The result showed, there was a variety of tools and agricultural machinery that have been produced and used by farmers to support national food security. The role of mechanization was needed to support national rice production and food security achievement.

Keywords: farming, Indonesia, mechanization, rice

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Authors: Geetanjali Panda, Suvrakanti Chakraborty

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In this paper, Newton-like descent methods are proposed for unconstrained optimization problems, which use q-derivatives of the gradient of an objective function. First, a local scheme is developed with alternative sufficient optimality condition, and then the method is extended to a global scheme. Moreover, a variant of practical Newton scheme is also developed introducing a real sequence. Global convergence of these schemes is proved under some mild conditions. Numerical experiments and graphical illustrations are provided. Finally, the performance profiles on a test set show that the proposed schemes are competitive to the existing first-order schemes for optimization problems.

Keywords: Descent algorithm, line search method, q calculus, Quasi Newton method

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Authors: Sofiane Bououden, Ilyes Boulkaibet

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In terms of security of the information signal, the meta-heuristic Penguins Search Optimization Algorithm (PeSOA) is applied to synchronize chaotic encryption communications in the case of sensitive dependence on initial conditions in chaotic generator oscillator. The objective of this paper is the use of the PeSOA algorithm to exploring search space with random and iterative processes for synchronization of symmetric keys in both transmission and reception. Simulation results show the effectiveness of the PeSOA algorithm in generating symmetric keys of the encryption process and synchronizing.

Keywords: meta-heuristic, PeSOA, chaotic systems, encryption, synchronization optimization

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Authors: N. Boontian

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Biological conversion of biomass to methane has received increasing attention in recent years. Grasses have been explored for their potential anaerobic digestion to methane. In this review, extensive literature data have been tabulated and classified. The influences of several parameters on the potential of these feedstocks to produce methane are presented. Lignocellulosic biomass represents a mostly unused source for biogas and ethanol production. Many factors, including lignin content, crystallinity of cellulose, and particle size, limit the digestibility of the hemicellulose and cellulose present in the lignocellulosic biomass. Pretreatments have used to improve the digestibility of the lignocellulosic biomass. Each pretreatment has its own effects on cellulose, hemicellulose and lignin, the three main components of lignocellulosic biomass. Solid-state anaerobic digestion (SS-AD) generally occurs at solid concentrations higher than 15%. In contrast, liquid anaerobic digestion (AD) handles feedstocks with solid concentrations between 0.5% and 15%. Animal manure, sewage sludge, and food waste are generally treated by liquid AD, while organic fractions of municipal solid waste (OFMSW) and lignocellulosic biomass such as crop residues and energy crops can be processed through SS-AD. An increase in operating temperature can improve both the biogas yield and the production efficiency, other practices such as using AD digestate or leachate as an inoculant or decreasing the solid content may increase biogas yield but have negative impact on production efficiency. Focus is placed on substrate pretreatment in anaerobic digestion (AD) as a means of increasing biogas yields using today’s diversified substrate sources.

Keywords: anaerobic digestion, lignocellulosic biomass, methane production, optimization, pretreatment

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Authors: E Tolufase

Abstract:

The demand, high costs and health implications of using energy derived from hydrocarbon compound have necessitated the continuous search for alternative source of energy. The World energy market is facing some challenges viz: depletion of fossil fuel reserves, population explosion, lack of energy security, economic and urbanization growth and also, in Nigeria some rural areas still depend largely on wood, charcoal, kerosene, petrol among others, as the sources of their energy. To overcome these short falls in energy supply and demand, as well as taking into consideration the risks from global climate change due to effect of greenhouse gas emissions and other pollutants from fossil fuels’ combustion, brought a lot of attention on efficiently harnessing the renewable energy sources. A very promising among the renewable energy resources for a clean energy technology for power production, vehicle and domestic usage is biogas. Therefore, optimization of biogas yield and quality is imperative. Hence, this study investigated yield and quality of biogas using low cost bio-digester and combination of various feed stocks referred to as co-digestion. Batch/Discontinuous Bio-digester type was used because it was cheap, easy, plausible and appropriate for different substrates used to get the desired results. Three substrates were used; cow dung, chicken droppings and lemon grass digested in five separate 21 litre digesters, A, B, C, D, and E and the gas collection system was designed using locally available materials. For single digestion we had; cow dung, chicken droppings, lemon grass, in Bio-digesters A, B, and C respectively, the co-digested three substrates in different mixed ratio 7:1:2 in digester D and E in ratio 5:3:2. The respective feed-stocks materials were collected locally, digested and analyzed in accordance with standard procedures. They were pre-fermented for a period of 10 days before being introduced into the digesters. They were digested for a retention period of 28 days, the physiochemical parameters namely; pressure, temperature, pH, volume of the gas collector system and volume of biogas produced were all closely monitored and recorded daily. The values of pH and temperature ranged 6.0 - 8.0, and 220C- 350C respectively. For the single substrate, bio-digester A(Cow dung only) produced biogas of total volume 0.1607m3(average volume of 0.0054m3 daily),while B (Chicken droppings ) produced 0.1722m3 (average of 0.0057m3 daily) and C (lemon grass) produced 0.1035m3 (average of 0.0035m3 daily). For the co-digested substrates in bio-digester D the total biogas produced was 0.2007m³ (average volume of 0.0067m³ daily) and bio-digester E produced 0.1991m³ (average volume of 0.0066m³ daily) It’s obvious from the results, that combining different substrates gave higher yields than when a singular feed stock was used and also mixing ratio played some roles in the yield improvement. Bio-digesters D and E contained the same substrates but mixed with different ratios, but higher yield was noticed in D with mixing ratio of 7:1:2 than in E with ratio 5:3:2.Therefore, co-digestion of substrates and mixing proportions are important factors for biogas production optimization.

Keywords: anaerobic, batch, biogas, biodigester, digestion, fermentation, optimization

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Authors: Phawin Sangsuvan, Chutimet Srinilta

Abstract:

This Paper presents the applications of Particle Swarm Optimization (PSO) Method for Thai optical character recognition (OCR). OCR consists of the pre-processing, character recognition and post-processing. Before enter into recognition process. The Character must be “Prepped” by pre-processing process. The PSO is an optimization method that belongs to the swarm intelligence family based on the imitation of social behavior patterns of animals. Route of each particle is determined by an individual data among neighborhood particles. The interaction of the particles with neighbors is the advantage of Particle Swarm to determine the best solution. So PSO is interested by a lot of researchers in many difficult problems including character recognition. As the previous this research used a Projection Histogram to extract printed digits features and defined the simple Fitness Function for PSO. The results reveal that PSO gives 67.73% for testing dataset. So in the future there can be explored enhancement the better performance of PSO with improve the Fitness Function.

Keywords: character recognition, histogram projection, particle swarm optimization, pattern recognition techniques

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Authors: B. Sellami, Y. Laskri, M. Belloufi

Abstract:

Conjugate gradient methods are an important class of methods for unconstrained optimization, especially for large-scale problems. Recently, they have been much studied. In this paper, a new family of conjugate gradient method is proposed for unconstrained optimization. This method includes the already existing two practical nonlinear conjugate gradient methods, which produces a descent search direction at every iteration and converges globally provided that the line search satisfies the Wolfe conditions. The numerical experiments are done to test the efficiency of the new method, which implies the new method is promising. In addition the methods related to this family are uniformly discussed.

Keywords: conjugate gradient method, global convergence, line search, unconstrained optimization

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Authors: Luz Stella Cadavid-Rodriguez, Viviana E. Castro-Lopez

Abstract:

Fish waste (FW) has a high content of potentially biodegradable components, so it is amenable to be digested anaerobically. In this line, anaerobic digestion (AD) of FW has been studied for biogas production. Nevertheless, intermediate products such as volatile fatty acids (VFA), generated during the acidogenic stage, have been scarce investigated, even though they have a high potential as a renewable source of carbon. In the literature, there are few studies about the Inoculum-Substrate (I/S) ratio on acidogenesis. On the other hand, it is well known that pH is a critical factor in the production of VFA. The optimum pH for the production of VFA seems to change depending on the substrate and can vary in a range between 5.25 and 11. Nonetheless, the literature about VFA production from protein-rich waste, such as FW, is scarce. In this context, it is necessary to deepen on the determination of the optimal operating conditions of acidogenic fermentation for VFA production from protein-rich waste. Therefore, the aim of this research was to optimize the volatile fatty acid production from artisanal fishing waste, studying the effect of pH and the I/S ratio on the acidogenic process. For this research, the inoculum used was a methanogenic sludge (MS) obtained from a UASB reactor treating wastewater of a slaughterhouse plant, and the FW was collected in the port of Tumaco (Colombia) from the local artisanal fishers. The acidogenic fermentation experiments were conducted in batch mode, in 500 mL glass bottles as anaerobic reactors, equipped with rubber stoppers provided with a valve to release biogas. The effective volume used was 300 mL. The experiments were carried out for 15 days at a mesophilic temperature of 37± 2 °C and constant agitation of 200 rpm. The effect of 3 pH levels: 5, 7, 9, coupled with five I/S ratios, corresponding to 0.20, 0.15, 0.10, 0.05, 0.00 was evaluated taking as a response variable the production of VFA. A complete randomized block design was selected for the experiments in a 5x3 factorial arrangement, with two repetitions per treatment. At the beginning and during the process, pH in the experimental reactors was adjusted to the corresponding values of 5, 7, and 9 using 1M NaOH or 1M H2SO4, as was appropriated. In addition, once the optimum I/S ratio was determined, the process was evaluated at this condition without pH control. The results indicated that pH is the main factor in the production of VFA, obtaining the highest concentration with neutral pH. By reducing the I/S ratio, as low as 0.05, it was possible to maximize VFA production. Thus, the optimum conditions found were natural pH (6.6-7.7) and I/S ratio of 0.05, with which it was possible to reach a maximum total VFA concentration of 70.3 g Ac/L, whose major components were acetic acid (35%) and butyric acid (32%). The findings showed that the acidogenic fermentation of FW is an efficient way of producing VFA and that the operating conditions can be simple and economical.

Keywords: acidogenesis, artisanal fishing waste, inoculum to substrate ratio, volatile fatty acids

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Authors: Mohammed Affanuddin H. Siddique, Jayesh S. Shukla, Chetan B. Meshram

Abstract:

The neural networks are one of the power tools of machine learning. After the invention of perceptron in early 1980's, the neural networks and its application have grown rapidly. Neural networks are a technique originally developed for pattern investigation. The structure of a neural network consists of neurons connected through synapse. Here, we have investigated the different algorithms and cost function reduction techniques for optimization of vertical axis wind turbine (VAWT) rotor blades. The aerodynamic force coefficients corresponding to the airfoils are stored in a database along with the airfoil coordinates. A forward propagation neural network is created with the input as aerodynamic coefficients and output as the airfoil co-ordinates. In the proposed algorithm, the hidden layer is incorporated into cost function having linear and non-linear error terms. In this article, it is observed that the ANNs (Artificial Neural Network) can be used for the VAWT’s optimization.

Keywords: VAWT, ANN, optimization, inverse design

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Authors: Nur Azzammudin Rahmat, Ismail Musirin, Ahmad Farid Abidin

Abstract:

Economic load dispatch is performed by the utilities in order to determine the best generation level at the most feasible operating cost. In order to guarantee satisfying energy delivery to the consumer, a precise calculation of generation level is required. In order to achieve accurate and practical solution, several considerations such as prohibited operating zones, valve-point effect and ramp-rate limit need to be taken into account. However, these considerations cause the optimization to become complex and difficult to solve. This research focuses on the valve-point effect that causes ripple in the fuel-cost curve. This paper also proposes Differential Evolution Immunized Ant Colony Optimization (DEIANT) in solving economic load dispatch problem with valve-point effect. Comparative studies involving DEIANT, EP and ACO are conducted on IEEE 30-Bus RTS for performance assessments. Results indicate that DEIANT is superior to the other compared methods in terms of calculating lower operating cost and power loss.

Keywords: ant colony optimization (ACO), differential evolution (DE), differential evolution immunized ant colony optimization (DEIANT), economic load dispatch (ELD)

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