Search results for: Integrated process planning and scheduling

Authors: Chun-guang Pan, Ying-wu Chen

Abstract:

Risk response planning is of importance for software project risk management (SPRM). In CMMI, risk management was in the third capability maturity level, which provides a framework for software project risk identification, assessment, risk planning, risk control. However, the CMMI-based SPRM currently lacks quantitative supporting tools, especially during the process of implementing software project risk planning. In this paper, an economic optimization model for selecting risk reduction actions in the phase of software project risk response planning is presented. Furthermore, an example taken from a Chinese software industry is illustrated to verify the application of this method. The research provides a risk decision method for project risk managers that can be used in the implementation of CMMI-based SPRM.

Keywords: Software project, risk management, CMMI, riskresponse planning.

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Authors: Florin Pop

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Simulation is a very powerful method used for highperformance and high-quality design in distributed system, and now maybe the only one, considering the heterogeneity, complexity and cost of distributed systems. In Grid environments, foe example, it is hard and even impossible to perform scheduler performance evaluation in a repeatable and controllable manner as resources and users are distributed across multiple organizations with their own policies. In addition, Grid test-beds are limited and creating an adequately-sized test-bed is expensive and time consuming. Scalability, reliability and fault-tolerance become important requirements for distributed systems in order to support distributed computation. A distributed system with such characteristics is called dependable. Large environments, like Cloud, offer unique advantages, such as low cost, dependability and satisfy QoS for all users. Resource management in large environments address performant scheduling algorithm guided by QoS constrains. This paper presents the performance evaluation of scheduling heuristics guided by different optimization criteria. The algorithms for distributed scheduling are analyzed in order to satisfy users constrains considering in the same time independent capabilities of resources. This analysis acts like a profiling step for algorithm calibration. The performance evaluation is based on simulation. The simulator is MONARC, a powerful tool for large scale distributed systems simulation. The novelty of this paper consists in synthetic analysis results that offer guidelines for scheduler service configuration and sustain the empirical-based decision. The results could be used in decisions regarding optimizations to existing Grid DAG Scheduling and for selecting the proper algorithm for DAG scheduling in various actual situations.

Keywords: Scheduling, Simulation, Performance Evaluation, QoS, Distributed Systems, MONARC

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Authors: Sangsuree Vasupongayya

Abstract:

Fair share objective has been included into the goaloriented parallel computer job scheduling policy recently. However, the previous work only presented the overall scheduling performance. Thus, the per-user performance of the policy is still lacking. In this work, the details of per-user fair share performance under the Tradeoff-fs(Tx:avgX) policy will be further evaluated. A basic fair share priority backfill policy namely RelShare(1d) is also studied. The performance of all policies is collected using an event-driven simulator with three real job traces as input. The experimental results show that the high demand users are usually benefited under most policies because their jobs are large or they have a lot of jobs. In the large job case, one job executed may result in over-share during that period. In the other case, the jobs may be backfilled for performances. However, the users with a mixture of jobs may suffer because if the smaller jobs are executing the priority of the remaining jobs from the same user will be lower. Further analysis does not show any significant impact of users with a lot of jobs or users with a large runtime approximation error.

Keywords: deviation, fair share, discrepancy search, priority scheduling.

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Authors: E. Golden Julie, S. Tamil Selvi, Y. Harold Robinson

Abstract:

Many Wireless Sensor Network (WSN) applications necessitate secure multicast services for the purpose of broadcasting delay sensitive data like video files and live telecast at fixed time-slot. This work provides a novel method to deal with end-to-end delay and drop rate of packets. Opportunistic Routing chooses a link based on the maximum probability of packet delivery ratio. Null Key Generation helps in authenticating packets to the receiver. Markov Decision Process based Adaptive Scheduling algorithm determines the time slot for packet transmission. Both theoretical analysis and simulation results show that the proposed protocol ensures better performance in terms of packet delivery ratio, average end-to-end delay and normalized routing overhead.

Keywords: Delay-sensitive data, Markovian Decision Process based Adaptive Scheduling, Opportunistic Routing, Digital Signature authentication.

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Authors: Bin Cai, Shilong Wang, Haibo Hu

Abstract:

The job shop scheduling problem (JSSP) is well known as one of the most difficult combinatorial optimization problems. This paper presents a hybrid genetic algorithm for the JSSP with the objective of minimizing makespan. The efficiency of the genetic algorithm is enhanced by integrating it with a local search method. The chromosome representation of the problem is based on operations. Schedules are constructed using a procedure that generates full active schedules. In each generation, a local search heuristic based on Nowicki and Smutnicki-s neighborhood is applied to improve the solutions. The approach is tested on a set of standard instances taken from the literature and compared with other approaches. The computation results validate the effectiveness of the proposed algorithm.

Keywords: Genetic algorithm, Job shop scheduling problem, Local search, Meta-heuristic algorithm

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Authors: Douglas A. Menezes, Isabel D. Nunes, Ulrich Schiel

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Most Virtual Learning Environments do not provide support mechanisms for the integrated planning, construction and follow-up of Instructional Design supported by Learning Analytic results. The present work aims to present an authoring tool that will be responsible for constructing the structure of an Instructional Design (ID), without the data being altered during the execution of the course. The visual interface aims to present the critical situations present in this ID, serving as a support tool for the course follow-up and possible improvements, which can be made during its execution or in the planning of a new edition of this course. The model for the ID is based on High-Level Petri Nets and the visualization forms are determined by the specific kind of the data generated by an e-course, a population of students generating sequentially dependent data.

Keywords: Educational data visualization, high-level petri nets, instructional design, learning analytics.

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Authors: Faris Elghaish, Sepehr Abrishami, Mark Gaterell, Richard Wise

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The collaboration and integration between all building information management (BIM) processes and tasks are necessary to ensure that all project objectives can be delivered. The literature review has been used to explore the state of the art BIM technologies to manage construction materials as well as the challenges which have faced the construction process using traditional methods. Thus, this paper aims to articulate a framework to integrate traditional material planning methods such as ABC analysis theory (Pareto principle) to analyse and categorise the project materials, as well as using independent material planning methods such as Economic Order Quantity (EOQ) and Fixed Order Point (FOP) into the BIM 4D, and 5D capabilities in order to articulate a dependent material planning cycle into BIM, which relies on the constructability method. Moreover, we build a model to connect between the material planning outputs and the BIM 4D and 5D data to ensure that all project information will be accurately presented throughout integrated and complementary BIM reporting formats. Furthermore, this paper will present a method to integrate between the risk management output and the material management process to ensure that all critical materials are monitored and managed under the all project stages. The paper includes browsers which are proposed to be embedded in any 4D BIM platform in order to predict the EOQ as well as FOP and alarm the user during the construction stage. This enables the planner to check the status of the materials on the site as well as to get alarm when the new order will be requested. Therefore, this will lead to manage all the project information in a single context and avoid missing any information at early design stage. Subsequently, the planner will be capable of building a more reliable 4D schedule by allocating the categorised material with the required EOQ to check the optimum locations for inventory and the temporary construction facilitates.

Keywords: Building information management, BIM, economic order quantity, fixed order point, BIM 4D, BIM 5D.

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Authors: Tadeusz Witkowski, Paweł Antczak, Arkadiusz Antczak

Abstract:

In the paper we discuss the influence of the route flexibility degree, the open rate of operations and the production type coefficient on makespan. The flexible job-open shop scheduling problem FJOSP (an extension of the classical job shop scheduling) is analyzed. For the analysis of the production process we used a hybrid heuristic of the GRASP (greedy randomized adaptive search procedure) with simulated annealing algorithm. Experiments with different levels of factors have been considered and compared. The GRASP+SA algorithm has been tested and illustrated with results for the serial route and the parallel one.

Keywords: Makespan, open shop, route flexibility, serial and parallel route, simulation modeling, type of production.

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Authors: Xiangbin Zhu

Abstract:

EDF (Early Deadline First) algorithm is a very important scheduling algorithm for real- time systems . The EDF algorithm assigns priorities to each job according to their absolute deadlines and has good performance when the real-time system is not overloaded. When the real-time system is overloaded, many misdeadlines will be produced. But these misdeadlines are not uniformly distributed, which usually focus on some tasks. In this paper, we present an adaptive fuzzy control scheduling based on EDF algorithm. The improved algorithm can have a rectangular distribution of misdeadline ratios among all real-time tasks when the system is overloaded. To evaluate the effectiveness of the improved algorithm, we have done extensive simulation studies. The simulation results show that the new algorithm is superior to the old algorithm.

Keywords: Fuzzy control, real-time systems, EDF, misdeadline ratio.

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Authors: Rupali, Anil Kumar Jaiswal

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Cloud computing can be defined as one of the prominent technologies that lets a user change, configure and access the services online. it can be said that this is a prototype of computing that helps in saving cost and time of a user practically the use of cloud computing can be found in various fields like education, health, banking etc.  Cloud computing is an internet dependent technology thus it is the major responsibility of Cloud Service Providers(CSPs) to care of data stored by user at data centers. Scheduling in cloud computing environment plays a vital role as to achieve maximum utilization and user satisfaction cloud providers need to schedule resources effectively.  Job scheduling for cloud computing is analyzed in the following work. To complete, recreate the task calculation, and conveyed scheduling methods CloudSim3.0.3 is utilized. This research work discusses the job scheduling for circulated processing condition also by exploring on this issue we find it works with minimum time and less cost. In this work two load balancing techniques have been employed: ‘Throttled stack adjustment policy’ and ‘Active VM load balancing policy’ with two brokerage services ‘Advanced Response Time’ and ‘Reconfigure Dynamically’ to evaluate the VM_Cost, DC_Cost, Response Time, and Data Processing Time. The proposed techniques are compared with Round Robin scheduling policy.

Keywords: Physical machines, virtual machines, support for repetition, self-healing, highly scalable programming model.

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Authors: Tomas Duranik, Juraj Ruzbarsky, Markus Stopper

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CONWIP (constant work-in-process) as a pull production system have been widely studied by researchers to date. The CONWIP pull production system is an alternative to pure push and pure pull production systems. It lowers and controls inventory levels which make the throughput better, reduces production lead time, delivery reliability and utilization of work. In this article a CONWIP pull production system was simulated. It was simulated push and pull planning system. To compare these systems via a production planning system (PPS) game were adjusted parameters of each production planning system. The main target was to reduce the total WIP and achieve throughput and delivery reliability to minimum values. Data was recorded and evaluated. A future state was made for real production of plastic components and the setup of the two indicators with CONWIP pull production system which can greatly help the company to be more competitive on the market.

Keywords: CONWIP, constant work in process, delivery reliability, hybrid production planning, PPS.

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Authors: P.S.Prakash, S.Selvan

Abstract:

Packet switched data network like Internet, which has traditionally supported throughput sensitive applications such as email and file transfer, is increasingly supporting delay-sensitive multimedia applications such as interactive video. These delaysensitive applications would often rather sacrifice some throughput for better delay. Unfortunately, the current packet switched network does not offer choices, but instead provides monolithic best-effort service to all applications. This paper evaluates Class Based Queuing (CBQ), Coordinated Earliest Deadline First (CEDF), Weighted Switch Deficit Round Robin (WSDRR) and RED-Boston scheduling schemes that is sensitive to delay bound expectations for variety of real time applications and an enhancement of WSDRR is proposed.

Keywords: QoS, Delay-sensitive, Queuing delay, Scheduling

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Authors: Danping Lin, C.K.M. Lee

Abstract:

Re-entrant scheduling is an important search problem with many constraints in the flow shop. In the literature, a number of approaches have been investigated from exact methods to meta-heuristics. This paper presents a genetic algorithm that encodes the problem as multi-level chromosomes to reflect the dependent relationship of the re-entrant possibility and resource consumption. The novel encoding way conserves the intact information of the data and fastens the convergence to the near optimal solutions. To test the effectiveness of the method, it has been applied to the resource-constrained re-entrant flow shop scheduling problem. Computational results show that the proposed GA performs better than the simulated annealing algorithm in the measure of the makespan

Keywords: Resource-constrained, re-entrant, genetic algorithm (GA), multi-level encoding

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Authors: Dharmendra Chourishi “Maitraya”, Sridevi Seshadri

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Bluetooth is a personal wireless communication technology and is being applied in many scenarios. It is an emerging standard for short range, low cost, low power wireless access technology. Current existing MAC (Medium Access Control) scheduling schemes only provide best-effort service for all masterslave connections. It is very challenging to provide QoS (Quality of Service) support for different connections due to the feature of Master Driven TDD (Time Division Duplex). However, there is no solution available to support both delay and bandwidth guarantees required by real time applications. This paper addresses the issue of how to enhance QoS support in a Bluetooth piconet. The Bluetooth specification proposes a Round Robin scheduler as possible solution for scheduling the transmissions in a Bluetooth Piconet. We propose an algorithm which will reduce the bandwidth waste and enhance the efficiency of network. We define token counters to estimate traffic of real-time slaves. To increase bandwidth utilization, a back-off mechanism is then presented for best-effort slaves to decrease the frequency of polling idle slaves. Simulation results demonstrate that our scheme achieves better performance over the Round Robin scheduling.

Keywords: Piconet, Medium Access Control, Polling algorithm, Scheduling, QoS, Time Division Duplex (TDD).

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Authors: Salam Saudagar, Ankit Kamboj, Niraj Mohan, Satgounda Patil, Nilesh Powar

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Task Assignment and Scheduling is a challenging Operations Research problem when there is a limited number of resources and comparatively higher number of tasks. The Cost Management team at Cummins needs to assign tasks based on a deadline and must prioritize some of the tasks as per business requirements. Moreover, there is a constraint on the resources that assignment of tasks should be done based on an individual skill level, that may vary for different tasks. Another constraint is for scheduling the tasks that should be evenly distributed in terms of number of working hours, which adds further complexity to this problem. The proposed greedy approach to solve assignment and scheduling problem first assigns the task based on management priority and then by the closest deadline. This is followed by an iterative selection of an available resource with the least allocated total working hours for a task, i.e. finding the local optimal choice for each task with the goal of determining the global optimum. The greedy approach task allocation is compared with a variant of Hungarian Algorithm, and it is observed that the proposed approach gives an equal allocation of working hours among the resources. The comparative study of the proposed approach is also done with manual task allocation and it is noted that the visibility of the task timeline has increased from 2 months to 6 months. An interactive dashboard app is created for the greedy assignment and scheduling approach and the tasks with more than 2 months horizon that were waiting in a queue without a delivery date initially are now analyzed effectively by the business with expected timelines for completion.

Keywords: Assignment, deadline, greedy approach, hungarian algorithm, operations research, scheduling.

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Authors: Liu Ji-Wei, Pei Yu-Liang, Liu Qian, Han Xiang, Zeng De-Liang

Abstract:

The economic and stable operation was affected seriously by coal quality disturbance for power plants. Based on model analysis, influence of the disturbance can be considered as gain change of control system. Power capability coefficient of coal was constructed to inhibit it. Accuracy of the coefficient was verified by operating data. Then coal quality disturbance free system based on gain scheduling was designed for coordinated control system. Simulation showed that, the strategy improved control quality obviously, and inhibited the coal quality disturbance.

Keywords: coordinate control system, coal quality disturbance, energy coefficient of coal quality, gain scheduling

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Authors: M. Heydari, S. A. Torabi

Abstract:

The problem of lot sizing, sequencing and scheduling multiple products in flow line production systems has been studied by several authors. Almost all of the researches in this area assumed that setup times and costs are sequence –independent even though sequence dependent setups are common in practice. In this paper we present a new mixed integer non linear program (MINLP) and a heuristic method to solve the problem in sequence dependent case. Furthermore, a genetic algorithm has been developed which applies this constructive heuristic to generate initial population. These two proposed solution methods are compared on randomly generated problems. Computational results show a clear superiority of our proposed GA for majority of the test problems.

Keywords: Economic lot scheduling problem, finite horizon, genetic algorithm, mixed zero-one nonlinear programming, sequence-dependent.

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Authors: Govind Sharan Dangayach, Himanshu Bhatt

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The paper attempts to overcome the fluctuations occurring in demand of the components in an automotive sector company. Resource and time being the strict constraints, the production is not able to match the pace of the fluctuating demand. So, we introduce some production schedules that help in meeting out the required demand. The merits and demerits of the approaches are also highlighted.

Keywords: Production scheduling, Demand rise, Capacity constrained resource (CCR), Overtime.

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Authors: Fatemeh Azimi, Razeeh Sadat Aboutalebi, Amir Abbas Najafi

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In this paper the multi-mode resource-constrained project scheduling problem with discounted cash flows is considered. Minimizing the makespan and maximization the net present value (NPV) are the two common objectives that have been investigated in the literature. We apply one evolutionary algorithm named multiobjective particle swarm optimization (MOPSO) to find Pareto front solutions. We used standard sets of instances from the project scheduling problem library (PSPLIB). The results are computationally compared respect to different metrics taken from the literature on evolutionary multi-objective optimization.

Keywords: Evolutionary multi-objective optimization makespan, multi-mode, resource constraint, net present value.

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Authors: Anis Gharbi

Abstract:

This paper considers the problem of scheduling maintenance actions for identical aircraft gas turbine engines. Each one of the turbines consists of parts which frequently require replacement. A finite inventory of spare parts is available and all parts are ready for replacement at any time. The inventory consists of both new and refurbished parts. Hence, these parts have different field lives. The goal is to find a replacement part sequencing that maximizes the time that the aircraft will keep functioning before the inventory is replenished. The problem is formulated as an identical parallel machine scheduling problem where the minimum completion time has to be maximized. Two models have been developed. The first one is an optimization model which is based on a 0-1 linear programming formulation, while the second one is an approximate procedure which consists in decomposing the problem into several two-machine subproblems. Each subproblem is optimally solved using the first model. Both models have been implemented using Lingo and have been tested on two sets of randomly generated data with up to 150 parts and 10 turbines. Experimental results show that the optimization model is able to solve only instances with no more than 4 turbines, while the decomposition procedure often provides near-optimal solutions within a maximum CPU time of 3 seconds.

Keywords: Aircraft turbines, Scheduling, Identical parallel machines, 0-1 linear programming, Heuristic.

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Authors: W. Wiyaratn, A. Watanapa

Abstract:

The objective of this research is to study plant layout of iron manufacturing based on the systematic layout planning pattern theory (SLP) for increased productivity. In this case study, amount of equipments and tools in iron production are studied. The detailed study of the plant layout such as operation process chart, flow of material and activity relationship chart has been investigated. The new plant layout has been designed and compared with the present plant layout. The SLP method showed that new plant layout significantly decrease the distance of material flow from billet cutting process until keeping in ware house.

Keywords: Plant layout, Systematic Layout Planning, Flowanalysis, Activity relationship chart

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Authors: Sunita Dhingra, Satinder Bal Gupta, Ranjit Biswas

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Multiprocessor task scheduling is a NP-hard problem and Genetic Algorithm (GA) has been revealed as an excellent technique for finding an optimal solution. In the past, several methods have been considered for the solution of this problem based on GAs. But, all these methods consider single criteria and in the present work, minimization of the bi-criteria multiprocessor task scheduling problem has been considered which includes weighted sum of makespan & total completion time. Efficiency and effectiveness of genetic algorithm can be achieved by optimization of its different parameters such as crossover, mutation, crossover probability, selection function etc. The effects of GA parameters on minimization of bi-criteria fitness function and subsequent setting of parameters have been accomplished by central composite design (CCD) approach of response surface methodology (RSM) of Design of Experiments. The experiments have been performed with different levels of GA parameters and analysis of variance has been performed for significant parameters for minimisation of makespan and total completion time simultaneously.

Keywords: Multiprocessor task scheduling, Design of experiments, Genetic Algorithm, Makespan, Total completion time.

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Authors: Sohrab Khanmohammadi, Raana Soltani Zarrin

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In this paper, a heuristic method for simultaneous rescue robot path-planning and mission scheduling is introduced based on project management techniques, multi criteria decision making and artificial potential fields path-planning. Groups of injured people are trapped in a disastrous situation. These people are categorized into several groups based on the severity of their situation. A rescue robot, whose ultimate objective is reaching injured groups and providing preliminary aid for them through a path with minimum risk, has to perform certain tasks on its way towards targets before the arrival of rescue team. A decision value is assigned to each target based on the whole degree of satisfaction of the criteria and duties of the robot toward the target and the importance of rescuing each target based on their category and the number of injured people. The resulted decision value defines the strength of the attractive potential field of each target. Dangerous environmental parameters are defined as obstacles whose risk determines the strength of the repulsive potential field of each obstacle. Moreover, negative and positive energies are assigned to the targets and obstacles, which are variable with respects to the factors involved. The simulation results show that the generated path for two cases studies with certain differences in environmental conditions and other risk factors differ considerably.

Keywords: Artificial potential field, GERT, path planning

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Authors: Wahyudin P. Syam, Ibrahim M. Al-Harkan

Abstract:

This study compares three meta heuristics to minimize makespan (Cmax) for Hybrid Flow Shop (HFS) Scheduling Problem with Parallel Machines. This problem is known to be NP-Hard. This study proposes three algorithms among improvement heuristic searches which are: Genetic Algorithm (GA), Simulated Annealing (SA), and Tabu Search (TS). SA and TS are known as deterministic improvement heuristic search. GA is known as stochastic improvement heuristic search. A comprehensive comparison from these three improvement heuristic searches is presented. The results for the experiments conducted show that TS is effective and efficient to solve HFS scheduling problems.

Keywords: Flow shop, genetic algorithm, simulated annealing, tabu search.

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Authors: S. Arun Rajan, S. Bhavani

Abstract:

Wireless sensor networks can be tiny, low cost, intelligent sensors connected with advanced communication systems. WSNs have pulled in significant consideration as a matter of fact that, industrial as well as medical solicitations employ these in monitoring targets, conservational observation, obstacle exposure, movement regulator etc. In these applications, sensor hubs are thickly sent in the unattended environment with little non-rechargeable batteries. This constraint requires energy-efficient systems to drag out the system lifetime. There are redundancies in data sent over the network. To overcome this, multiple virtual spine scheduling has been presented. Such networks problems are called Maximum Lifetime Backbone Scheduling (MLBS) problems. Though this sleep wake cycle reduces radio usage, improvement can be made in the path in which the group heads stay selected. Cluster head selection with emphasis on geometrical relation of the system will enhance the load sharing among the nodes. Also the data are analyzed to reduce redundant transmission. Multi-hop communication will facilitate lighter loads on the network.

Keywords: WSN, wireless sensor networks, MLBS, maximum lifetime backbone scheduling.

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Authors: M. Esmaeeli Shahrakht, A. Kazemi

Abstract:

Due to uncertainty of wind velocity, wind power generators don’t have deterministic output power. Utilizing wind power generation and thermal power plants together create new concerns for operation engineers of power systems. In this paper, a model is presented to implement the uncertainty of load and generated wind power which can be utilized in power system operation planning. Stochastic behavior of parameters is simulated by generating scenarios that can be solved by deterministic method. A mixed-integer linear programming method is used for solving deterministic generation scheduling problem. The proposed approach is applied to a 12-unit test system including 10 thermal units and 2 wind farms. The results show affectivity of piecewise linear model in unit commitment problems. Also using linear programming causes a considerable reduction in calculation times and guarantees convergence to the global optimum. Neglecting the uncertainty of wind velocity causes higher cost assessment of generation scheduling.

Keywords: Load uncertainty, linear programming, scenario generation, unit commitment, wind farm.

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Authors: Sally A. Brown

Abstract:

Over the last 30 years, researchers have developed models or frameworks to provide a more structured understanding of the reading comprehension process. Cognitive information processing models and social cognitive theories both provide frameworks to inform reading comprehension instruction. The purpose of this paper is to (a) provide an overview of the historical development of reading comprehension theory, (b) review the literature framed by cognitive information processing, social cognitive, and integrated reading comprehension theories, and (c) demonstrate how these frameworks inform instruction. As integrated models of reading can guide the interpretation of various factors related to student learning, an integrated framework designed by the researcher will be presented. Results indicated that features of cognitive processing and social cognitivism theory—represented in the integrated framework—highlight the importance of the role of the teacher. This model can aide teachers in not only improving reading comprehension instruction but in identifying areas of challenge for students.

Keywords: Explicit instruction, integrated models of reading comprehension, reading comprehension, teacher’s role.

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Authors: E. Koyuncu

Abstract:

The problem of Order Acceptance and Scheduling (OAS) is defined as a joint decision of which orders to accept for processing and how to schedule them. Any linear programming model representing real-world situation involves the parameters defined by the decision maker in an uncertain way or by means of language statement. Fuzzy data can be used to incorporate vagueness in the real-life situation. In this study, a fuzzy mathematical model is proposed for a single machine OAS problem, where the orders are defined by their fuzzy due dates, fuzzy processing times, and fuzzy sequence dependent setup times. The signed distance method, one of the fuzzy ranking methods, is used to handle the fuzzy constraints in the model.

Keywords: Fuzzy mathematical programming, fuzzy ranking, order acceptance, single machine scheduling.

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Authors: Rahmad Wisnu Wardana, Eakachai Warinsiriruk, Sutep Joy-A-Ka

Abstract:

Selecting the most suitable welding process usually depends on experiences or common application in similar companies. However, this approach generally ignores many criteria that can be affecting the suitable welding process selection. Therefore, knowledge automation through knowledge-based systems will significantly improve the decision-making process. The aims of this research propose integrated data envelopment analysis (DEA) and fuzzy credibility constrained programming approach for identifying the best welding process for stainless steel storage tank in the food and beverage industry. The proposed approach uses fuzzy concept and credibility measure to deal with uncertain data from experts' judgment. Furthermore, 12 parameters are used to determine the most appropriate welding processes among six competitive welding processes.

Keywords: Welding process selection, data envelopment analysis, fuzzy credibility constrained programming, storage tank.

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Authors: Xiangbin Zhu

Abstract:

Advances in computing applications in recent years have prompted the demand for more flexible scheduling models for QoS demand. Moreover, in practical applications, partly violated temporal constraints can be tolerated if the violation meets certain distribution. So we need extend the traditional Liu and Lanland model to adapt to these circumstances. There are two extensions, which are the (m, k)-firm model and Window-Constrained model. This paper researches on weakly hard real-time constraints and their combination to support QoS. The fact that a practical application can tolerate some violations of temporal constraint under certain distribution is employed to support adaptive QoS on the open real-time system. The experiment results show these approaches are effective compared to traditional scheduling algorithms.

Keywords: Weakly Hard Real-Time, Real-Time, Scheduling, Quality of Service.

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