Search results for: order picking problem

Authors: Revaz Gvelesiani

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The problem of compliance between the state economic policy and entrepreneurial policy of businesses is primarily manifested in the contradictions related to the congruence between entrepreneurship development and self-development strategies. Among various types (financial, monetary, social, etc.) of the state economic policy aiming at the development of entrepreneurship, economic order policy is of special importance. Its goal is to set the framework for both public and private economic activities and achieve coherence between the societal value system and the formation of the economic order framework. Economic order policy, in its turn, involves intrinsic contradiction between the social and the competitive order. Competitive order is oriented on the principle of success, while social order _ on the criteria of need satisfaction, which contradicts, at least partly, to the principles of success. Thus within the economic order policy, on the one hand, the state makes efforts to form social order and expand its frontiers, while, on the other hand, market is determined to establish functioning competitive order and ensure its realization. Locating the adequate spaces for and setting the rational border between the state (social order) and the private (competitive order) activities, represents the phenomenon of the decisive importance from the entrepreneurship development strategy standpoint. In the countries where the above mentioned spaces and borders are “set” correctly, entrepreneurship agents (small, medium-sized and large businesses) achieve great success by means of seizing the respective segments and maintaining the leading positions in the internal, the European and the world markets for a long time. As for the entrepreneurship self-development strategy, above all, it involves: •market identification; •interactions with consumers; •continuous innovations; •competition strategy; •relationships with partners; •new management philosophy, etc. The analysis of compliance between the entrepreneurship strategy and entrepreneurship culture should be the reference point for any kind of internationalization in order to avoid shocks of cultural nature and the economic backwardness. Stabilization can be achieved only when the employee actions reflect the existing culture and the new contents of culture (targeted culture) is turned into the implicit consciousness of the personnel. The future leaders should learn how to manage different cultures. Entrepreneurship can be managed successfully if its strategy and culture are coherent. However, not rarely enterprises (organizations) show various forms of violation of both personal and team actions. If personal and team non-observances appear as the form of influence upon the culture, it will lead to global destruction of the system and structure. This is the entrepreneurship culture pathology that complicates to achieve compliance between the entrepreneurship strategy and entrepreneurship culture. Thus, the intrinsic contradictions of entrepreneurship development and self-development strategies complicate the task of reaching compliance between the state economic policy and the company entrepreneurship policy: on the one hand, there is a contradiction between the social and the competitive order within economic order policy and on the other hand, the contradiction exists between entrepreneurship strategy and entrepreneurship culture within entrepreneurship policy.

Keywords: economic order policy, entrepreneurship, development contradictions, self-development contradictions

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Authors: Tohari Ahmad, Hudan Studiawan, Iwang Aryadinata, Royyana M. Ijtihadie, Waskitho Wibisono

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A manual voting system has been implemented worldwide. It has some weaknesses which may decrease the legitimacy of the voting result. An electronic voting system is introduced to minimize this weakness. It has been able to provide a better result, in terms of the total time taken in the voting process and accuracy. Nevertheless, people may be reluctant to go to the polling location because of some reasons, such as distance and time. In order to solve this problem, mobile voting is implemented by utilizing mobile devices. There are many mobile voting architectures available. Overall, authenticity of the users is the common problem of all voting systems. There must be a mechanism which can verify the users’ authenticity such that only verified users can give their vote once; others cannot vote. In this paper, a challenge response-based authentication is proposed by utilizing properties of the users, for example, something they have and know. In terms of speed, the proposed system provides good result, in addition to other capabilities offered by the system.

Keywords: authentication, data protection, mobile voting, security

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Authors: Graham Brooks, Belaisha Bin Belaisha, Hakkyong Kim

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The problem of preventing and/or reducing corruption is a major international problem. This paper, however, specifically focuses on how organisations in Dubai are tackling the problem of money laundering. This research establishes that Dubai has a clear international anti-money laundering framework but suffers from some national weaknesses such as diverse anti-money laundering working practice, lack of communication, sharing information and disparate organisational vested self-interest.

Keywords: corruption, governance, money laundering, prevention, strategies

Procedia PDF Downloads 253

Authors: El Hassene Osmani, Mounir Haddou, Naceurdine Bensalem

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In this paper, we investigate optimal control problems governed by semilinear elliptic variational inequalities involving constraints on the state, and more precisely, the obstacle problem. We present a relaxed formulation for the problem using smoothing functions. Since we adopt a numerical point of view, we first relax the feasible domain of the problem, then using both mathematical programming methods and penalization methods, we get optimality conditions with smooth Lagrange multipliers. Some numerical experiments using IPOPT algorithm (Interior Point Optimizer) are presented to verify the efficiency of our approach.

Keywords: complementarity problem, IPOPT, Lagrange multipliers, mathematical programming, optimal control, smoothing methods, variationally inequalities

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Authors: Medani Khaled Ben Oualid

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Most of researchers solved and analyzed the ORPD problem in the normal conditions. However, network collapses appear in contingency conditions. In this paper, ORPD under several contingencies is presented using the proposed method WOA. To ensure viability of the power system in contingency conditions, several critical cases are simulated in order to prevent and prepare the power system to face such situations. The results obtained are carried out in IEEE 30 bus test system for the solution of ORPD problem in which control of bus voltages, tap position of transformers and reactive power sources are involved. Moreover, another method, namely, Particle Swarm Optimization with Time Varying Acceleration Coefficient (PSO-TVAC) has been compared with the proposed technique. Simulation results indicate that the proposed WOA gives remarkable solution in terms of effectiveness in case of outages.

Keywords: optimal reactive power dispatch, metaheuristic techniques, whale optimization algorithm, real power loss minimization, contingency conditions

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Authors: Mukadder Baran, Mustafa Sözbilir

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The purpose of this paper is to investigate the applicabillity of the Context- and Problem-Based Learning (CPBL) in general chemistry course to the subject of “Thermodynamics” but also the influence of CPBL on students’ achievement, retention of knowledge, their interest, attitudes, motivation and problem-solving skills. The study group included 13 freshman students who were selected with the sampling method appropriate to the purpose among those taking the course of General Chemistry within the Program of Medical Laboratory Techniques at Hakkari University. The application was carried out in the Spring Term of the academic year of 2012-2013. As the data collection tool, Lesson Observation form were used. In the light of the observations held, it was revealed that CPBL increased the students’ intragroup and intergroup communication skills as well as their self-confidence and developed their skills in time management, presentation, reporting, and technology use; and that they were able to relate chemistry to daily life. Depending on these findings, it could be suggested that the area of use of CPBL be widened; that seminars related to constructive methods be organized for teachers. In this way, it is believed that students will not be passive in the group any longer. In addition, it was concluded that in order to avoid the negative effects of the socio-cultural structure on the education system, research should be conducted in places where there is socio-cultural obstacles, and appropriate solutions should be suggested and put into practice.

Keywords: chemistry, education, science, context-based learning

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Authors: Jayson Vicente

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The young men and women of Philippine Military Academy Cadet Corps Armed Forces of the Philippines (PMA CCAFP) are bred to be front liners and last line of defense during war and times of peace; as such, they must be equipped with the most practical and most effective combat-ready Martial Arts and Combative skills to effectively fulfill their duty, as well as to protect and safeguard themselves to continue serving the people and their country. This study shall assess the current Martial Arts and Combative Program of the PMA CCAFP using descriptive methodology by interviews and floating questionnaires. The current Martial Arts and Combative Program of the PMA CCAFP with all of the subjects involved are more sports inclined rather than combat-equipped. Picking the best from each subject used in the program, this study seeks to recommend improvements or create a better Martial Arts and Combative Program that will satisfy the objective of producing Martial Arts combatant graduates. A good Martial Arts and Combative Program for PMA is essential to prepare them for what lies ahead, which is unforgiving and no rules to pacify threat.

Keywords: combative, martial arts, military, program

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Authors: C. E. Nugraheni, L. Abednego

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This paper is concerned with minimization of mean tardiness and flow time in a real single machine production scheduling problem. Two variants of genetic algorithm as meta-heuristic are combined with hyper-heuristic approach are proposed to solve this problem. These methods are used to solve instances generated with real world data from a company. Encouraging results are reported.

Keywords: hyper-heuristics, evolutionary algorithms, production scheduling, meta-heuristic

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Authors: Prateek Chharia, Biswa Bhusan Ghosh

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Graph coloring is one of the prominent concepts in graph coloring. It can be defined as a coloring of the various regions of the graph such that all the constraints are fulfilled. In this paper various graphs coloring approaches like greedy coloring, Heuristic search for maximum independent set and graph coloring using edge table is described. Graph coloring can be used in various real time applications like student time tabling generation, Sudoku as a graph coloring problem, GSM phone network.

Keywords: graph coloring, greedy coloring, heuristic search, edge table, sudoku as a graph coloring problem

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Authors: Akrem Sellami, Imed Riadh Farah

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Hyperspectral imagery (HSI) typically provides a wealth of information captured in a wide range of the electromagnetic spectrum for each pixel in the image. Hence, a pixel in HSI is a high-dimensional vector of intensities with a large spectral range and a high spectral resolution. Therefore, the semantic interpretation is a challenging task of HSI analysis. We focused in this paper on object classification as HSI semantic interpretation. However, HSI classification still faces some issues, among which are the following: The spatial variability of spectral signatures, the high number of spectral bands, and the high cost of true sample labeling. Therefore, the high number of spectral bands and the low number of training samples pose the problem of the curse of dimensionality. In order to resolve this problem, we propose to introduce the process of dimensionality reduction trying to improve the classification of HSI. The presented approach is a semi-supervised band selection method based on spatial hypergraph embedding model to represent higher order relationships with different weights of the spatial neighbors corresponding to the centroid of pixel. This semi-supervised band selection has been developed to select useful bands for object classification. The presented approach is evaluated on AVIRIS and ROSIS HSIs and compared to other dimensionality reduction methods. The experimental results demonstrate the efficacy of our approach compared to many existing dimensionality reduction methods for HSI classification.

Keywords: dimensionality reduction, hyperspectral image, semantic interpretation, spatial hypergraph

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Authors: G. M. Komaki, S. Mobin, E. Teymourian, S. Sheikh

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This paper addresses minimizing the makespan of the distributed permutation flow shop scheduling problem. In this problem, there are several parallel identical factories or flowshops each with series of similar machines. Each job should be allocated to one of the factories and all of the operations of the jobs should be performed in the allocated factory. This problem has recently gained attention and due to NP-Hard nature of the problem, metaheuristic algorithms have been proposed to tackle it. Majority of the proposed algorithms require large computational time which is the main drawback. In this study, a general variable neighborhood search algorithm (GVNS) is proposed where several time-saving schemes have been incorporated into it. Also, the GVNS uses the sophisticated method to change the shaking procedure or perturbation depending on the progress of the incumbent solution to prevent stagnation of the search. The performance of the proposed algorithm is compared to the state-of-the-art algorithms based on standard benchmark instances.

Keywords: distributed permutation flow shop, scheduling, makespan, general variable neighborhood search algorithm

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Authors: K. Djellabi, M. E. H. Latreche

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The induction heating phenomenon depends on various factors, making the problem highly nonlinear. The mathematical analysis of this problem in most cases is very difficult and it is reduced to simple cases. Another knowledge of induction heating systems is generated in production environments, but these trial-error procedures are long and expensive. The numerical models of induction heating problem are another approach to reduce abovementioned drawbacks. This paper deals with the simulation model of induction heating problem. The simulation model of induction heating system in COMSOL Multiphysics is created. In this work we present results of numerical simulations of induction heating process in pieces of cylindrical shapes, in an inductor with four coils. The modeling of the inducting heating process was made with the software COMSOL Multiphysics Version 4.2a, for the study we present the temperature charts.

Keywords: induction heating, electromagnetic field, inductor, numerical simulation, finite element

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Authors: Zelalem Fantahun

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Part-of-speech tagging is the process of assigning a part-of-speech or other lexical class marker to each word into naturally occurring text. Part-of-speech tagging is the most fundamental and basic task almost in all natural language processing. In natural language processing, the problem of providing large amount of manually annotated data is a knowledge acquisition bottleneck. Since, Amharic is one of under-resourced language, the availability of tagged corpus is the bottleneck problem for natural language processing especially for POS tagging. A promising direction to tackle this problem is to provide a system that does not require manually tagged data. In unsupervised learning, the learner is not provided with classifications. Unsupervised algorithms seek out similarity between pieces of data in order to determine whether they can be characterized as forming a group. This paper explicates the development of unsupervised part-of-speech tagger using K-Means clustering for Amharic language since large amount of data is produced in day-to-day activities. In the development of the tagger, the following procedures are followed. First, the unlabeled data (raw text) is divided into 10 folds and tokenization phase takes place; at this level, the raw text is chunked at sentence level and then into words. The second phase is feature extraction which includes word frequency, syntactic and morphological features of a word. The third phase is clustering. Among different clustering algorithms, K-means is selected and implemented in this study that brings group of similar words together. The fourth phase is mapping, which deals with looking at each cluster carefully and the most common tag is assigned to a group. This study finds out two features that are capable of distinguishing one part-of-speech from others these are morphological feature and positional information and show that it is possible to use unsupervised learning for Amharic POS tagging. In order to increase performance of the unsupervised part-of-speech tagger, there is a need to incorporate other features that are not included in this study, such as semantic related information. Finally, based on experimental result, the performance of the system achieves a maximum of 81% accuracy.

Keywords: POS tagging, Amharic, unsupervised learning, k-means

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Authors: M. S. Annie Christi

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Transportation Problem (TP) is based on supply and demand of commodities transported from one source to the different destinations. Usual methods for finding solution of TPs are North-West Corner Rule, Least Cost Method Vogel’s Approximation Method etc. The transportation costs tend to vary at each time. We can use fuzzy numbers which would give solution according to this situation. In this study the Best Candidate Method (BCM) is applied. For ranking Centroid Ranking Technique (CRT) and Robust Ranking Technique have been adopted to transform the fuzzy TP and the above methods are applied to EDWARDS Vacuum Company, Crawley, in West Sussex in the United Kingdom. A Comparative study is also given. We see that the transportation cost can be minimized by the application of CRT under BCM.

Keywords: best candidate method, centroid ranking technique, fuzzy transportation problem, robust ranking technique, transportation problem

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Authors: Norhayati Mohd Rasip, Abd. Samad Hasan Basari , Nuzulha Khilwani Ibrahim, Burairah Hussin

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The allocation of working schedule especially for shift environment is hard to fulfill its fairness among them. In the case of nurse scheduling, to set up the working time table for them is time consuming and complicated, which consider many factors including rules, regulation and human factor. The scenario is more complicated since most nurses are women which have personnel constraints and maternity leave factors. The undesirable schedule can affect the nurse productivity, social life and the absenteeism can significantly as well affect patient's life. This paper aimed to enhance the scheduling process by utilizing the particle swarm optimization in order to solve nurse scheduling problem. The result shows that the generated multiple initial schedule is fulfilled the requirements and produces the lowest cost of constraint violation.

Keywords: nurse scheduling, particle swarm optimisation, nurse rostering, hard and soft constraint

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Authors: Sajed A. Habib

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Problem-based learning (PBL) is a student-centered pedagogy that originated in the medical field and has also been used extensively in other knowledge disciplines with recognized advantages and limitations. PBL has been used in various undergraduate engineering programs with mixed outcomes. The current fourth industrial revolution (digital era or Industry 4.0) has made it essential for many science and engineering students to receive effective training in advanced courses such as industrial automation and robotics. This paper presents a case study at Assumption University of Thailand, where a PBL-like approach was used to teach some aspects of automation and robotics to selected groups of undergraduate engineering students. These students were given some basic level training in automation prior to participating in a subsequent training session in order to solve technical problems with increased complexity. The participating students’ evaluation of the training sessions in terms of learning effectiveness, skills enhancement, and incremental knowledge following the problem-solving session was captured through a follow-up survey consisting of 14 questions and a 5-point scoring system. From the most recent training event, an overall 70% of the respondents indicated that their skill levels were enhanced to a much greater level than they had had before the training, whereas 60.4% of the respondents from the same event indicated that their incremental knowledge following the session was much greater than what they had prior to the training. The instructor-facilitator involved in the training events suggested that this method of learning was more suitable for senior/advanced level students than those at the freshmen level as certain skills to effectively participate in such problem-solving sessions are acquired over a period of time, and not instantly.

Keywords: automation, industry 4.0, model-based design training, problem-based learning

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Authors: Raoul Ouambo Tobou, Alexis Kuitche, Marcel Edoun

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The FWM (Finite Window Method) is a new numerical meshfree technique for solving problems defined either in terms of PDEs (Partial Differential Equation) or by a set of conservation/equilibrium laws. The principle behind the FWM is that in such problem each element of the concerned domain is interacting with its neighbors and will always try to adapt to keep in equilibrium with respect to those neighbors. This leads to a very simple and robust problem solving scheme, well suited for transfer problems. In this work, we have applied the FWM to an unsteady scalar convection-diffusion equation. Despite its simplicity, it is well known that convection-diffusion problems can be challenging to be solved numerically, especially when convection is highly dominant. This has led researchers to set the scalar convection-diffusion equation as a benchmark one used to analyze and derive the required conditions or artifacts needed to numerically solve problems where convection and diffusion occur simultaneously. We have shown here that the standard FWM can be used to solve convection-diffusion equations in a robust manner as no adjustments (Upwinding or Artificial Diffusion addition) were required to obtain good results even for high Peclet numbers and coarse space and time steps. A comparison was performed between the FWM scheme and both a first order implicit Finite Volume Scheme (Upwind scheme) and a third order implicit Finite Volume Scheme (QUICK Scheme). The results of the comparison was that for equal space and time grid spacing, the FWM yields a much better precision than the used Finite Volume schemes, all having similar computational cost and conditioning number.

Keywords: Finite Window Method, Convection-Diffusion, Numerical Technique, Convergence

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Authors: David Hasurungan

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This paper objective is to assess the power distribution reliability improvement by retrofitting obsolete vacuum contactor. The case study in Badak Liquefied Natural Gas (LNG) plant is presented in this paper. To support plant operational, Badak LNG is equipped with 4.16 kV switchgear for supplying the storage and loading facilities, utilities facilities, and train facilities. However, there is a problem in two switch gears of sixteen switch gears. The problem is the obsolescence issue in its vacuum contactor. Not only that, but the same switchgear also has suffered from electrical fault due to contact fingering misalignment. In order to improve the reliability in switchgear, the vacuum contactor retrofit project is done. The retrofit will introduce new vacuum contactor design. The comparison between existing design and the new design is presented in this paper. Meanwhile, The reliability assessment and calculation are performed using software Reliasoft 7.

Keywords: reliability, obsolescence, retrofit, vacuum contactor

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Authors: Mohanad Al-Behadili, Djamila Ouelhadj

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In this paper, a specific type of vehicle routing problem under stochastic demand (SVRP) is considered. This problem is of great importance because it models for many of the real world vehicle routing applications. This paper used a robust optimisation model to solve the problem along with the novel Simulation-Particle Swarm Optimisation (Sim-PSO) approach. The proposed Sim-PSO approach is based on the hybridization of the Monte Carlo simulation technique with the PSO algorithm. A comparative study between the proposed model and the Sim-PSO approach against other solution methods in the literature has been given in this paper. This comparison including the Analysis of Variance (ANOVA) to show the ability of the model and solution method in solving the complicated SVRP. The experimental results show that the proposed model and Sim-PSO approach has a significant impact on the obtained solution by providing better quality solutions comparing with well-known algorithms in the literature.

Keywords: stochastic vehicle routing problem, robust optimisation model, Monte Carlo simulation, particle swarm optimisation

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Authors: Lei Zhao, Zhe Yuan, Wenyue Kuang

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This paper studies two-warehouse inventory models for a deteriorating item considering that the demand is influenced by inventory levels. The problem mainly focuses on the optimal order policy and the optimal order cycle with inventory-level-dependent demand in two-warehouse system for retailers. It considers the different deterioration rates and the inventory holding costs in owned warehouse (OW) and rented warehouse (RW), and the conditions of transportation cost, allowed shortage and partial backlogging. Two inventory models are formulated: last-in first-out (LIFO) model and first-in-first-out (FIFO) model based on the policy choices of LIFO and FIFO, and a comparative analysis of LIFO model and FIFO model is made. The study finds that the FIFO policy is more in line with realistic operating conditions. Especially when the inventory holding cost of OW is high, and there is no difference or big difference between deterioration rates of OW and RW, the FIFO policy has better applicability. Meanwhile, this paper considers the differences between the effects of warehouse and shelf inventory levels on demand, and then builds retailers’ inventory decision model and studies the factors of the optimal order quantity, the optimal order cycle and the average inventory cost per unit time. To minimize the average total cost, the optimal dispatching policies are provided for retailers’ decisions.

Keywords: FIFO model, inventory-level-dependent, LIFO model, two-warehouse inventory

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Authors: Adilson Elias Xavier, Otto Corrêa Rotunno Filho, Paulo Canedo De Magalhães

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This paper addresses the issue of automatic parameter estimation in conceptual rainfall-runoff (CRR) models. Due to threshold structures commonly occurring in CRR models, the associated mathematical optimization problems have the significant characteristic of being strongly non-differentiable. In order to face this enormous task, the resolution method proposed adopts a smoothing strategy using a special C∞ differentiable class function. The final estimation solution is obtained by solving a sequence of differentiable subproblems which gradually approach the original conceptual problem. The use of this technique, called Hyperbolic Smoothing Method (HSM), makes possible the application of the most powerful minimization algorithms, and also allows for the main difficulties presented by the original CRR problem to be overcome. A set of computational experiments is presented for the purpose of illustrating both the reliability and the efficiency of the proposed approach.

Keywords: rainfall-runoff models, automatic calibration, hyperbolic smoothing method

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Authors: Ahmed Tarek, Ahmed Alveed

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Vehicle routing problem is a well-known re-search avenue in computing. Modern vehicle routing is more focused with the GPS-based coordinate system, as the state-of-the-art vehicle, and trucking systems are equipped with digital navigation. In this paper, a new two dimensional coordinate-based algorithm for addressing the vehicle routing problem for a supply chain network is proposed and explored, and the algorithm is compared with other available, and recently devised heuristics. For the algorithms discussed, which includes the pro-posed coordinate-based search heuristic as well, the advantages and the disadvantages associated with the heuristics are explored. The proposed algorithm is studied from the stand point of a small supermarket chain delivery network that supplies to its stores in four different states around the East Coast area, and is trying to optimize its trucking delivery cost. Minimizing the delivery cost for the supply network of a supermarket chain is important to ensure its business success.

Keywords: coordinate-based optimal routing, Hamiltonian Circuit, heuristic algorithm, traveling salesman problem, vehicle routing problem

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Authors: Ebrahim Asadi-Gangraj

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Hybrid flow shop scheduling problem (HFS) contains sequencing in a flow shop where, at any stage, there exist one or more related or unrelated parallel machines. This production system is a common manufacturing environment in many real industries, such as the steel manufacturing, ceramic tile manufacturing, and car assembly industries. In this research, a mixed integer linear programming (MILP) model is presented for the hybrid flow shop scheduling problem, in which, the objective consists of minimizing the maximum completion time (makespan). For this purpose, a Benders Decomposition (BD) method is developed to solve the research problem. The proposed approach is tested on some test problems, small to moderate scale. The experimental results show that the Benders decomposition approach can solve the hybrid flow shop scheduling problem in a reasonable time, especially for small and moderate-size test problems.

Keywords: hybrid flow shop, mixed integer linear programming, Benders decomposition, makespan

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Authors: Sarmistha Singh

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An analysis of trend of urbanization and urban poverty in recent decades is showing that a distinctly reducing rural poverty and increasing in urban areas. It can be argued that the higher the urbanization fuelled by the urban migration to city, which is picking up people from less skilled, education so they faced obstacle to enter into the mainstream economy of city. The share of workforce in economy is higher; in contrast it remains as negligence. At the same time, less wages, absence of social security, social dialogue make them insecure. The vulnerability in their livelihood found. So the paper explores the relation of urbanization and urban poverty in the city, in other words how the urbanization process affecting the urban space in creating the number of poor people in the city. The central focus is the mobility of people with less education and skilled with motive of job search and better livelihood. In many studies found the higher the urbanization and higher the urban poverty in city. In other words, poverty is the impact of urbanization. The strategy of urban inequality through ‘dispersal of concentration’ by the World Bank and others, need to be examined.

Keywords: urbanization, mobility, urban poverty, informal settlements, informal worker

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Authors: Fernando L. P. Santos, Luiz G. Lyra, Helenice O. Florentino, Daniela R. Cantane

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Dengue is a febrile infectious disease caused by a virus of the family Flaviridae. It is transmitted by the bite of mosquitoes, usually of the genus Aedes aegypti. It occurs in tropical and subtropical areas of the world. This disease has been a major public health problem worldwide, especially in tropical countries such as Brazil, and its incidence has increased in recent years. Dengue is a subject of intense research. Efficient forms of mosquito control must be considered. In this work, the mono-objective optimal control problem was solved for analysing the dengue disease problem. Chemical and biological controls were considered in the mathematical aspect. This model describes the dynamics of mosquitoes in water and winged phases. We applied the genetic algorithms (GA) to obtain optimal strategies for the control of dengue. Numerical simulations have been performed to verify the versatility and the applicability of this algorithm. On the basis of the present results we may recommend the GA to solve optimal control problem with a large region of feasibility.

Keywords: genetic algorithm, dengue, Aedes aegypti, biological control, chemical control

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Authors: Fanqiang Kong, Chending Bian

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In this work, we exploit two assumed properties of the abundances of the observed signatures (endmembers) in order to reconstruct the abundances from hyperspectral data. Joint-sparsity is the first property of the abundances, which assumes the adjacent pixels can be expressed as different linear combinations of same materials. The second property is rank-deficiency where the number of endmembers participating in hyperspectral data is very small compared with the dimensionality of spectral library, which means that the abundances matrix of the endmembers is a low-rank matrix. These assumptions lead to an optimization problem for the sparse unmixing model that requires minimizing a combined l_2,p-norm and nuclear norm. We propose a variable splitting and augmented Lagrangian algorithm to solve the optimization problem. Experimental evaluation carried out on synthetic and real hyperspectral data shows that the proposed method outperforms the state-of-the-art algorithms with a better spectral unmixing accuracy.

Keywords: hyperspectral unmixing, joint-sparse, low-rank representation, abundance estimation

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Authors: Min Kyung An

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In this paper, we study the data collection problem in Wireless Sensor Networks (WSNs) adopting the two interference models: The graph model and the more realistic physical interference model known as Signal-to-Interference-Noise-Ratio (SINR). The main issue of the problem is to compute schedules with the minimum number of timeslots, that is, to compute the minimum latency schedules, such that data from every node can be collected without any collision or interference to a sink node. While existing works studied the problem with unit-sized and unbounded-sized message models, we investigate the problem with the bounded-sized message model, and introduce a constant factor approximation algorithm. To the best known of our knowledge, our result is the first result of the data collection problem with bounded-sized model in both interference models.

Keywords: data collection, collision-free, interference-free, physical interference model, SINR, approximation, bounded-sized message model, wireless sensor networks

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Authors: Mohammad Soltani Renani

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The problem of evil is one of the heated battlegrounds of the idea of theism and its critics. Since time immemorial and in various philosophical schools and religions, the belief in an Omniscient, Omnipotent, and Absolutely Good God has been considered inconsistent with the existence of the evil in the universe. The theist thinkers have generally adopted one of the following four ways for answering this problem: denial of the existence of evil or considering it to be relative, privation theory of evil, attribution of evil to something other than God, and depiction of an alternative picture of God. Defense or criticism of these alternative answers have given rise to an extensive and unending dispute. However, evaluation of the presupposition and context upon/in which a question is raised precedes offering an answer to it. This point in the discussion of the problem of evil is of paramount importance for both parties, i.e., questioners and answerers, that the attributes of knowledge, power, love, good-will, among others, can be supposed to be infinite only in the essence of the attributed and the domain of potentiality but what can be realized in the domain of actuality is always finite. Therefore, infinite nature of Divine Attributes and realization of evil belong to two spheres. Divine Attributes are infinite (absolute) in Divine Essence, but when they are created, each one becomes bounded by the other. This boundedness is a result of the state of being surrounded of the attributes by each other in finite world of possibility. Evil also appears in this limited world. This inconsistency leads to the collapse of the problem of evil from within: the place of infinity of the Divine Attributes, in the words of Muslim mystics, lies in the Holiest Manifestation [Feyze Aqdas] while evil emerges in the Holy Manifestation where the Divine Attributes become bounded by each other. This idea is neither a new answer to the problem of evil nor a defense of theism; rather it reveals a logical inconsistency in the discussion of the problem of evil.

Keywords: problem of evil, infinity of divine attributes, boundedness of divine attributes, holiest manifestation, holy manifestation

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Authors: Balgaisha Mukanova, Tolkyn Mirgalikyzy

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Theory of interpretation of electromagnetic fields studied in the electrical prospecting with direct current is mainly developed for the case of a horizontal surface observation. However in practice we often have to work in difficult terrain surface. Conducting interpretation without the influence of topography can cause non-existent anomalies on sections. This raises the problem of studying the impact of different shapes of ground surface relief on the results of electrical prospecting's research. This research examines the numerical solutions of the direct problem of electrical prospecting for two-dimensional and three-dimensional media, taking into account the terrain. The problem is solved using the method of integral equations. The density of secondary currents on the relief surface is obtained.

Keywords: ground surface relief, method of integral equations, numerical method, electromagnetic

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Authors: Carol Okigbo

Abstract:

Mathematical problem solving has long been accorded an important place in mathematics curricula at every education level in both advanced and emerging economies. Its classroom approaches have varied, such as teaching for problem-solving, teaching about problem-solving, and teaching mathematics through problem-solving. It requires engaging in tasks for which the solution methods are not eminent, making sense of problems and persevering in solving them by exhibiting processes, strategies, appropriate attitude, and adequate exposure. Teachers play important roles in helping students acquire competency in problem-solving; thus, they are expected to be good problem-solvers and have proper conceptions of problem-solving. Studies show that teachers’ conceptions influence their decisions about what to teach and how to teach. Therefore, how teachers view their roles in teaching problem-solving will depend on their pedagogical conceptions of problem-solving. If teaching problem-solving is a major component of secondary school mathematics instruction, as recommended by researchers and mathematics educators, then it is necessary to establish teachers’ conceptions, what they do, and how they approach problem-solving. This study is designed to determine secondary school teachers’ conceptions regarding mathematical problem solving, its current situation, how teachers’ conceptions relate to their demographics, as well as the interaction patterns in the mathematics classroom. There have been many studies of mathematics problem solving, some of which addressed teachers’ conceptions using single-method approaches, thereby presenting only limited views of this important phenomenon. To address the problem more holistically, this study adopted an integrated mixed methods approach which involved a quantitative survey, qualitative analysis of open-ended responses, and ethnographic observations of teachers in class. Data for the analysis came from a random sample of 327 secondary school mathematics teachers in two Nigerian states - Anambra State and Enugu State who completed a 45-item questionnaire. Ten of the items elicited demographic information, 11 items were open-ended questions, and 25 items were Likert-type questions. Of the 327 teachers who responded to the questionnaires, 37 were randomly selected and observed in their classes. Data analysis using ANOVA, t-tests, chi-square tests, and open coding showed that the teachers had different conceptions about problem-solving, which fall into three main themes: practice on exercises and word application problems, a process of solving mathematical problems, and a way of teaching mathematics. Teachers reported that no period is set aside for problem-solving; typically, teachers solve problems on the board, teach problem-solving strategies, and allow students time to struggle with problems on their own. The result shows a significant difference between male and female teachers’ conception of problems solving, a significant relationship among teachers’ conceptions and academic qualifications, and teachers who have spent ten years or more teaching mathematics were significantly different from the group with seven to nine years of experience in terms of their conceptions of problem-solving.

Keywords: conceptions, education, mathematics, problem solving, teacher

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