Tsung-Che Chiang | National Taiwan Normal University (original) (raw)

Papers by Tsung-Che Chiang

Research paper thumbnail of Efficient Architecture For Island Genetic Algorithm in Reconfigurable Hardware

ABSTRACT A novel VLSI architecture for an island genetic algorithm (GA) is presented in this pape... more ABSTRACT A novel VLSI architecture for an island genetic algorithm (GA) is presented in this paper. The island GA is based on steady-state GA for reducing the hardware resources consumption. Alook-up table based fast string migration architecture is proposed for lowering the computational overhead while enhancing the performance for the island GA. As compared with its single-island GA hardware counterpart, the proposed architecture attains superior performance with less computation time subject to the same total population size. In addition, the proposed architecture has significantly lower computational time as compared with its software counterparts running on cluster computer with multithreading for GA-based optimization.

Research paper thumbnail of Evolutionary many-objective optimization by MO-NSGA-II with enhanced mating selection

2014 IEEE Congress on Evolutionary Computation (CEC), 2014

Many-objective optimization deals with problems with more than three objectives. The rapid growth... more Many-objective optimization deals with problems with more than three objectives. The rapid growth of non-dominated solutions with the increase of the number of objectives weakens the search ability of Pareto-dominance-based multiobjective evolutionary algorithms. MO-NSGA-II strengthens its dominance-based predecessor, NSGA-II, by guiding the search process with reference points. In this paper, we further improve MO-NSGA-II by enhancing its mating selection mechanism with a hierarchical selection and a neighborhood concept based on the reference points. Experimental results confirm that the proposed ideas lead to better solution quality.

Research paper thumbnail of A Virtual Preemption Paradigm for Using Priority Rules to Solve Job Shop Scheduling Problems

Proceedings of the 2005 IEEE International Conference on Robotics and Automation, 2005

To solve job shop scheduling problems, the priority rule is one of the most popular approach. It ... more To solve job shop scheduling problems, the priority rule is one of the most popular approach. It has the appeal because of simplicity, efficiency and effectiveness. However, the paradigm conventionally used to apply priority rules has a certain flaw. In this paper, we first point out this flaw and then propose a paradigm to remove it. A rule is also

Research paper thumbnail of An ant colony optimization algorithm for multi-objective clustering in mobile ad hoc networks

2014 IEEE Congress on Evolutionary Computation (CEC), 2014

Due to the proliferation of sma and the developments in wireless communicat networks (MANETs) are... more Due to the proliferation of sma and the developments in wireless communicat networks (MANETs) are gaining more and recent years. Routing in MANETs is a cha when the network contains a large numbe clustering technique is a popular method to o in MANETs. It divides the network into sev assigns a cluster head to each cluster for intra communication. Clustering is NP-hard and multiple objectives. In this paper we propose a colony optimization (ACO) algorithm to multiobjective optimization problem. A new e proposed to reduce the size of search space, an scheme is proposed to generate higheffectively. Experimental results show that better than several benchmark approaches.

Research paper thumbnail of Using dispatching rules for job shop scheduling with due date-based objectives

Proceedings 2006 IEEE International Conference on Robotics and Automation, 2006. ICRA 2006., 2006

This paper addresses the job shop scheduling problem with the due date-based objectives including... more This paper addresses the job shop scheduling problem with the due date-based objectives including the tardy rate, the mean tardiness, and the maximum tardiness. The focused approach is the dispatching rules. Eighteen dispatching rules are selected from the literature, and their features and design concepts are discussed. Then a dispatching rule is proposed with the goal as achieving good and balanced performance when more than one objective is concerned at the same time. First, it realizes three good design principles recognized from the existing rules. Second, it introduces a due date extension procedure to solve a problem of negative allowance time. Third, a job candidate reduction mechanism is developed to make the rule computationally efficient. At last, a comprehensive simulation study is conducted with the eighteen existing rules as the benchmarks. The experimental results verify the superiority of the proposed rule, especially on the tardy rate and the mean tardiness.

Research paper thumbnail of A Simulation Study on Dispatching Rules in Semiconductor Wafer Fabrication Facilities with Due Date-based Objectives

2006 IEEE International Conference on Systems, Man and Cybernetics, 2006

This paper addresses the lot scheduling problem in the semiconductor wafer fabrication facilities... more This paper addresses the lot scheduling problem in the semiconductor wafer fabrication facilities. We provide a simulation study to examine the performance of sixteen existing dispatching rules on the tardy rate, mean tardiness, and the maximum tardiness. A public and representative test bed, the MIMAC (measurement and improvement of manufacturing capacities) test bed is used. The best rules with respect

Research paper thumbnail of Colored timed Petri-net and GA based approach to modeling and scheduling for wafer probe center

2003 IEEE International Conference on Robotics and Automation (Cat. No.03CH37422), 2003

In this paper, we propose an architecture to simulate Wafer Probe. We use a modeling tool named C... more In this paper, we propose an architecture to simulate Wafer Probe. We use a modeling tool named CTPN (Colored-Timed Petri Nets) to model all testing flow. With CTPN model, we can predict the deliveiy date of any specific product under some scheduling policies efficiently and precisely. In the scheduling phase, we combine hvo popular methods to construct

Research paper thumbnail of Design of modern elevator group control systems

Proceedings 2002 IEEE International Conference on Robotics and Automation (Cat. No.02CH37292), 2002

The advantages of our EGCS are shown through extensive simulation results. We make a comparison b... more The advantages of our EGCS are shown through extensive simulation results. We make a comparison between our EGCS and the previous one, which shows that our results are quite satisfactory and superiol:

Research paper thumbnail of Multiobjective Job Shop Scheduling using Genetic Algorithm with Cyclic Fitness Assignment

2006 IEEE International Conference on Evolutionary Computation, 2006

A job shop scheduling problem with total tardiness and the maximum tardiness as objectives is add... more A job shop scheduling problem with total tardiness and the maximum tardiness as objectives is addressed. We solve it by a rule-coded genetic algorithm. Characteristics of three existing fitness assignment mechanisms are identified and then combined through the proposed cyclic fitness assignment mechanism. Experiments are conducted on a public benchmark problem set, and the results show that the proposed algorithm outperforms the existing ones.

Research paper thumbnail of An iterative refining mechanism for general job shop scheduling problems

IEEE International Conference on Automation Science and Engineering, 2005., 2005

This paper addresses the general job shop scheduling problem with the objective as how to increas... more This paper addresses the general job shop scheduling problem with the objective as how to increase the meet-due-date rate. An iterative schedule refining mechanism is proposed, which iteratively adjusts the estimation of the remaining processing times of jobs in a dynamic and stage-specific manner. The refining mechanism is applied to a recently proposed sequencing heuristic and the integrated approach shows satisfactory performance through a comprehensive simulation study. Besides, we also show that the proposed refining mechanism can bring much improvement to several conventional rules.

Research paper thumbnail of Parameter tuning of production scheduling rules by an ant system-embedded genetic algorithm

Research paper thumbnail of Multiobjective permutation flow shop scheduling using a memetic algorithm with an NEH-based local search

… of the 5th international conference on …, 2009

Abstract In this paper we address scheduling of the permutation flow shop with minimization of ma... more Abstract In this paper we address scheduling of the permutation flow shop with minimization of makespan and total flow time as the objectives. We propose a memetic algorithm (MA) to search for the set of nondominated solutions (the Pareto optimal solutions). The proposed ...

Research paper thumbnail of Multiobjective job shop scheduling using memetic algorithm and shifting bottleneck procedure

Computational Intelligence in …, 2009

In this work, the multiobjective job shop scheduling problem is addressed. The objectives under c... more In this work, the multiobjective job shop scheduling problem is addressed. The objectives under consideration are minimization of makespan and total tardiness. An integration of dispathing rules, Shifting Bottleneck procedure, and multiobjective memetic algorithm is proposed. The proposed approach significantly outperforms pure dispatching rule and rule-encoded memetic algorithm. In comparison with an existing benchmark approach on eight classical job shop problem instances, the proposed approach reports promising results and updates a large portion of the best known Pareto optimal solutions.

Research paper thumbnail of A memetic algorithm for minimizing total weighted tardiness on parallel batch machines with incompatible job families and dynamic job arrival

Computers & Operations Research, 2010

This paper addresses a scheduling problem motivated by scheduling of diffusion operations in the ... more This paper addresses a scheduling problem motivated by scheduling of diffusion operations in the wafer fabrication facility. In the target problem, jobs arrive at the batch machines at different time instants, and only jobs belonging to the same family can be processed together. Parallel batch machine scheduling typically consists of three types of decisions-batch forming, machine assignment, and batch sequencing. We propose a memetic algorithm with a new genome encoding scheme to search for the optimal or near-optimal batch formation and batch sequence simultaneously. Machine assignment is resolved in the proposed decoding scheme. Crossover and mutation operators suitable for the proposed encoding scheme are also devised. Through the experiment with 4860 problem instances of various characteristics including the number of machines, the number of jobs, and so on, the proposed algorithm demonstrates its advantages over a recently proposed benchmark algorithm in terms of both solution quality and computational efficiency.

Research paper thumbnail of NNMA: An effective memetic algorithm for solving multiobjective permutation flow shop scheduling problems

Expert Systems With Applications, 2011

The permutation flow shop scheduling problem is addressed in this paper. Two objectives, minimiza... more The permutation flow shop scheduling problem is addressed in this paper. Two objectives, minimization of makespan and total flow time, are considered. We propose a memetic algorithm, called NNMA, by integrating a general multiobjective evolutionary algorithm (NSGA-II) with a problem-specific heuristic (NEH). We take NEH as a local improving procedure in NNMA and propose several adaptations including the acceptance criterion and job-insertion ordering to deal with multiple objectives and to improve its performance. We test the performance of NNMA using 90 public problem instances with different problem scales, and compare its performance with 23 algorithms. The experimental results show that our NNMA provides close performance for 30 small-scale instances and better performance for 50 medium- and large-scale instances. Furthermore, more than 70% of the net set of non-dominated solutions is updated by NNMA for these 50 instances.► We integrate NSGA-II and NEH into an MA, where NEH serves as a local search procedure. ► We investigate job extraction, job ordering, and neighbor acceptance in NEH-based local search. ► Our approach updates more than 70% of net sets of non-dominated solutions for 50 public instances. ► Observations on the distribution of non-dominated solutions are given.

Research paper thumbnail of A knowledge-based evolutionary algorithm for the multiobjective vehicle routing problem with time windows

This paper addresses the multiobjective vehicle routing problem with time windows (MOVRPTW).

Research paper thumbnail of A simple and effective evolutionary algorithm for multiobjective flexible job shop scheduling

This paper addresses the multiobjective flexible job shop scheduling problem (MOFJSP) regarding m... more This paper addresses the multiobjective flexible job shop scheduling problem (MOFJSP) regarding minimizing the makespan, total workload, and maximum workload. The problem is solved in a Pareto manner, whose goal is to seek for the set of Pareto optimal solutions. We propose a multiobjective evolutionary algorithm, which utilizes effective genetic operators and maintains population diversity carefully. A main feature of the proposed algorithm is its simplicity -it needs only two parameters. Performance of our algorithm is compared with seven state-of-the-art algorithms on fifteen popular benchmark instances. Only our algorithm can find 70% or more nondominated solutions for every instance.

Research paper thumbnail of Enhancing rule-based scheduling in wafer fabrication facilities by evolutionary algorithms: Review and opportunity

Scheduling is a critical and challenging task in manufacturing systems, especially in largescale ... more Scheduling is a critical and challenging task in manufacturing systems, especially in largescale complex systems like wafer fabrication facilities. Although evolutionary algorithms (EAs) have demonstrated many successful applications in the field of manufacturing scheduling, there are very few studies on scheduling of wafer fabs using EAs. Dispatching rules are one of the most common techniques for fab scheduling. In this paper, we present six ways of applying EAs for enhancing the rule-based scheduling system. We provide potential EA-based solutions and review relevant literature. Many of the mentioned viewpoints can serve as new research topics for both researchers in the fields of scheduling and evolutionary computation (EC). Several general EC techniques including multiobjective optimization, expensive optimization, and parallelization are also introduced and shown to be helpful to fab scheduling.

Research paper thumbnail of Static and dynamic minimum energy broadcast problem in wireless ad-hoc networks: A PSO-based approach and analysis

In this paper, we address the minimum energy broadcast (MEB) problem in wireless ad-hoc networks ... more In this paper, we address the minimum energy broadcast (MEB) problem in wireless ad-hoc networks (WANETs). The researches in WANETs have attracted significant attentions, and one of the most critical issues in WSNs is minimization of energy consumption. In WANETs the packets have to be transported from a given source node to all other nodes in the network, and the objective of the MEB problem is to minimize the total transmission power consumption. A hybrid algorithm based on particle swarm optimization (PSO) and local search is presented to solve the MEB problem. A power degree encoding is proposed to reflect the extent of transmission power level and is used to define the particle position in PSO. We also analyze a well-known local search mechanism, r-shrink, and propose an improved version, the intensified r-shrink. In order to solve the dynamic MEB problem with node removal/insertion, this paper provides an effective simple heuristic, Conditional Incremental Power (CIP), to reconstruct the broadcast network efficiently. The promising results indicate the potential of the proposed methods for practical use.

Research paper thumbnail of Flexible Job Shop Scheduling Using a Multiobjective Memetic Algorithm

This paper addresses the flexible job shop scheduling problem with minimization of the makespan, ... more This paper addresses the flexible job shop scheduling problem with minimization of the makespan, maximum machine workload, and total machine workload as the objectives. A multiobjective memetic algorithm is proposed. It belongs to the integrated approach, which deals with the routing and sequencing sub-problems together. Dominance-based and aggregation-based fitness assignment methods are used in the parts of genetic algorithm and local search, respectively. The local search procedure follows the framework of variable neighborhood descent algorithm. The proposed algorithm is compared with three benchmark algorithms using fifteen classic problem instances. Its performance is better in terms of the number and quality of the obtained solutions.

Research paper thumbnail of Efficient Architecture For Island Genetic Algorithm in Reconfigurable Hardware

ABSTRACT A novel VLSI architecture for an island genetic algorithm (GA) is presented in this pape... more ABSTRACT A novel VLSI architecture for an island genetic algorithm (GA) is presented in this paper. The island GA is based on steady-state GA for reducing the hardware resources consumption. Alook-up table based fast string migration architecture is proposed for lowering the computational overhead while enhancing the performance for the island GA. As compared with its single-island GA hardware counterpart, the proposed architecture attains superior performance with less computation time subject to the same total population size. In addition, the proposed architecture has significantly lower computational time as compared with its software counterparts running on cluster computer with multithreading for GA-based optimization.

Research paper thumbnail of Evolutionary many-objective optimization by MO-NSGA-II with enhanced mating selection

2014 IEEE Congress on Evolutionary Computation (CEC), 2014

Many-objective optimization deals with problems with more than three objectives. The rapid growth... more Many-objective optimization deals with problems with more than three objectives. The rapid growth of non-dominated solutions with the increase of the number of objectives weakens the search ability of Pareto-dominance-based multiobjective evolutionary algorithms. MO-NSGA-II strengthens its dominance-based predecessor, NSGA-II, by guiding the search process with reference points. In this paper, we further improve MO-NSGA-II by enhancing its mating selection mechanism with a hierarchical selection and a neighborhood concept based on the reference points. Experimental results confirm that the proposed ideas lead to better solution quality.

Research paper thumbnail of A Virtual Preemption Paradigm for Using Priority Rules to Solve Job Shop Scheduling Problems

Proceedings of the 2005 IEEE International Conference on Robotics and Automation, 2005

To solve job shop scheduling problems, the priority rule is one of the most popular approach. It ... more To solve job shop scheduling problems, the priority rule is one of the most popular approach. It has the appeal because of simplicity, efficiency and effectiveness. However, the paradigm conventionally used to apply priority rules has a certain flaw. In this paper, we first point out this flaw and then propose a paradigm to remove it. A rule is also

Research paper thumbnail of An ant colony optimization algorithm for multi-objective clustering in mobile ad hoc networks

2014 IEEE Congress on Evolutionary Computation (CEC), 2014

Due to the proliferation of sma and the developments in wireless communicat networks (MANETs) are... more Due to the proliferation of sma and the developments in wireless communicat networks (MANETs) are gaining more and recent years. Routing in MANETs is a cha when the network contains a large numbe clustering technique is a popular method to o in MANETs. It divides the network into sev assigns a cluster head to each cluster for intra communication. Clustering is NP-hard and multiple objectives. In this paper we propose a colony optimization (ACO) algorithm to multiobjective optimization problem. A new e proposed to reduce the size of search space, an scheme is proposed to generate higheffectively. Experimental results show that better than several benchmark approaches.

Research paper thumbnail of Using dispatching rules for job shop scheduling with due date-based objectives

Proceedings 2006 IEEE International Conference on Robotics and Automation, 2006. ICRA 2006., 2006

This paper addresses the job shop scheduling problem with the due date-based objectives including... more This paper addresses the job shop scheduling problem with the due date-based objectives including the tardy rate, the mean tardiness, and the maximum tardiness. The focused approach is the dispatching rules. Eighteen dispatching rules are selected from the literature, and their features and design concepts are discussed. Then a dispatching rule is proposed with the goal as achieving good and balanced performance when more than one objective is concerned at the same time. First, it realizes three good design principles recognized from the existing rules. Second, it introduces a due date extension procedure to solve a problem of negative allowance time. Third, a job candidate reduction mechanism is developed to make the rule computationally efficient. At last, a comprehensive simulation study is conducted with the eighteen existing rules as the benchmarks. The experimental results verify the superiority of the proposed rule, especially on the tardy rate and the mean tardiness.

Research paper thumbnail of A Simulation Study on Dispatching Rules in Semiconductor Wafer Fabrication Facilities with Due Date-based Objectives

2006 IEEE International Conference on Systems, Man and Cybernetics, 2006

This paper addresses the lot scheduling problem in the semiconductor wafer fabrication facilities... more This paper addresses the lot scheduling problem in the semiconductor wafer fabrication facilities. We provide a simulation study to examine the performance of sixteen existing dispatching rules on the tardy rate, mean tardiness, and the maximum tardiness. A public and representative test bed, the MIMAC (measurement and improvement of manufacturing capacities) test bed is used. The best rules with respect

Research paper thumbnail of Colored timed Petri-net and GA based approach to modeling and scheduling for wafer probe center

2003 IEEE International Conference on Robotics and Automation (Cat. No.03CH37422), 2003

In this paper, we propose an architecture to simulate Wafer Probe. We use a modeling tool named C... more In this paper, we propose an architecture to simulate Wafer Probe. We use a modeling tool named CTPN (Colored-Timed Petri Nets) to model all testing flow. With CTPN model, we can predict the deliveiy date of any specific product under some scheduling policies efficiently and precisely. In the scheduling phase, we combine hvo popular methods to construct

Research paper thumbnail of Design of modern elevator group control systems

Proceedings 2002 IEEE International Conference on Robotics and Automation (Cat. No.02CH37292), 2002

The advantages of our EGCS are shown through extensive simulation results. We make a comparison b... more The advantages of our EGCS are shown through extensive simulation results. We make a comparison between our EGCS and the previous one, which shows that our results are quite satisfactory and superiol:

Research paper thumbnail of Multiobjective Job Shop Scheduling using Genetic Algorithm with Cyclic Fitness Assignment

2006 IEEE International Conference on Evolutionary Computation, 2006

A job shop scheduling problem with total tardiness and the maximum tardiness as objectives is add... more A job shop scheduling problem with total tardiness and the maximum tardiness as objectives is addressed. We solve it by a rule-coded genetic algorithm. Characteristics of three existing fitness assignment mechanisms are identified and then combined through the proposed cyclic fitness assignment mechanism. Experiments are conducted on a public benchmark problem set, and the results show that the proposed algorithm outperforms the existing ones.

Research paper thumbnail of An iterative refining mechanism for general job shop scheduling problems

IEEE International Conference on Automation Science and Engineering, 2005., 2005

This paper addresses the general job shop scheduling problem with the objective as how to increas... more This paper addresses the general job shop scheduling problem with the objective as how to increase the meet-due-date rate. An iterative schedule refining mechanism is proposed, which iteratively adjusts the estimation of the remaining processing times of jobs in a dynamic and stage-specific manner. The refining mechanism is applied to a recently proposed sequencing heuristic and the integrated approach shows satisfactory performance through a comprehensive simulation study. Besides, we also show that the proposed refining mechanism can bring much improvement to several conventional rules.

Research paper thumbnail of Parameter tuning of production scheduling rules by an ant system-embedded genetic algorithm

Research paper thumbnail of Multiobjective permutation flow shop scheduling using a memetic algorithm with an NEH-based local search

… of the 5th international conference on …, 2009

Abstract In this paper we address scheduling of the permutation flow shop with minimization of ma... more Abstract In this paper we address scheduling of the permutation flow shop with minimization of makespan and total flow time as the objectives. We propose a memetic algorithm (MA) to search for the set of nondominated solutions (the Pareto optimal solutions). The proposed ...

Research paper thumbnail of Multiobjective job shop scheduling using memetic algorithm and shifting bottleneck procedure

Computational Intelligence in …, 2009

In this work, the multiobjective job shop scheduling problem is addressed. The objectives under c... more In this work, the multiobjective job shop scheduling problem is addressed. The objectives under consideration are minimization of makespan and total tardiness. An integration of dispathing rules, Shifting Bottleneck procedure, and multiobjective memetic algorithm is proposed. The proposed approach significantly outperforms pure dispatching rule and rule-encoded memetic algorithm. In comparison with an existing benchmark approach on eight classical job shop problem instances, the proposed approach reports promising results and updates a large portion of the best known Pareto optimal solutions.

Research paper thumbnail of A memetic algorithm for minimizing total weighted tardiness on parallel batch machines with incompatible job families and dynamic job arrival

Computers & Operations Research, 2010

This paper addresses a scheduling problem motivated by scheduling of diffusion operations in the ... more This paper addresses a scheduling problem motivated by scheduling of diffusion operations in the wafer fabrication facility. In the target problem, jobs arrive at the batch machines at different time instants, and only jobs belonging to the same family can be processed together. Parallel batch machine scheduling typically consists of three types of decisions-batch forming, machine assignment, and batch sequencing. We propose a memetic algorithm with a new genome encoding scheme to search for the optimal or near-optimal batch formation and batch sequence simultaneously. Machine assignment is resolved in the proposed decoding scheme. Crossover and mutation operators suitable for the proposed encoding scheme are also devised. Through the experiment with 4860 problem instances of various characteristics including the number of machines, the number of jobs, and so on, the proposed algorithm demonstrates its advantages over a recently proposed benchmark algorithm in terms of both solution quality and computational efficiency.

Research paper thumbnail of NNMA: An effective memetic algorithm for solving multiobjective permutation flow shop scheduling problems

Expert Systems With Applications, 2011

The permutation flow shop scheduling problem is addressed in this paper. Two objectives, minimiza... more The permutation flow shop scheduling problem is addressed in this paper. Two objectives, minimization of makespan and total flow time, are considered. We propose a memetic algorithm, called NNMA, by integrating a general multiobjective evolutionary algorithm (NSGA-II) with a problem-specific heuristic (NEH). We take NEH as a local improving procedure in NNMA and propose several adaptations including the acceptance criterion and job-insertion ordering to deal with multiple objectives and to improve its performance. We test the performance of NNMA using 90 public problem instances with different problem scales, and compare its performance with 23 algorithms. The experimental results show that our NNMA provides close performance for 30 small-scale instances and better performance for 50 medium- and large-scale instances. Furthermore, more than 70% of the net set of non-dominated solutions is updated by NNMA for these 50 instances.► We integrate NSGA-II and NEH into an MA, where NEH serves as a local search procedure. ► We investigate job extraction, job ordering, and neighbor acceptance in NEH-based local search. ► Our approach updates more than 70% of net sets of non-dominated solutions for 50 public instances. ► Observations on the distribution of non-dominated solutions are given.

Research paper thumbnail of A knowledge-based evolutionary algorithm for the multiobjective vehicle routing problem with time windows

This paper addresses the multiobjective vehicle routing problem with time windows (MOVRPTW).

Research paper thumbnail of A simple and effective evolutionary algorithm for multiobjective flexible job shop scheduling

This paper addresses the multiobjective flexible job shop scheduling problem (MOFJSP) regarding m... more This paper addresses the multiobjective flexible job shop scheduling problem (MOFJSP) regarding minimizing the makespan, total workload, and maximum workload. The problem is solved in a Pareto manner, whose goal is to seek for the set of Pareto optimal solutions. We propose a multiobjective evolutionary algorithm, which utilizes effective genetic operators and maintains population diversity carefully. A main feature of the proposed algorithm is its simplicity -it needs only two parameters. Performance of our algorithm is compared with seven state-of-the-art algorithms on fifteen popular benchmark instances. Only our algorithm can find 70% or more nondominated solutions for every instance.

Research paper thumbnail of Enhancing rule-based scheduling in wafer fabrication facilities by evolutionary algorithms: Review and opportunity

Scheduling is a critical and challenging task in manufacturing systems, especially in largescale ... more Scheduling is a critical and challenging task in manufacturing systems, especially in largescale complex systems like wafer fabrication facilities. Although evolutionary algorithms (EAs) have demonstrated many successful applications in the field of manufacturing scheduling, there are very few studies on scheduling of wafer fabs using EAs. Dispatching rules are one of the most common techniques for fab scheduling. In this paper, we present six ways of applying EAs for enhancing the rule-based scheduling system. We provide potential EA-based solutions and review relevant literature. Many of the mentioned viewpoints can serve as new research topics for both researchers in the fields of scheduling and evolutionary computation (EC). Several general EC techniques including multiobjective optimization, expensive optimization, and parallelization are also introduced and shown to be helpful to fab scheduling.

Research paper thumbnail of Static and dynamic minimum energy broadcast problem in wireless ad-hoc networks: A PSO-based approach and analysis

In this paper, we address the minimum energy broadcast (MEB) problem in wireless ad-hoc networks ... more In this paper, we address the minimum energy broadcast (MEB) problem in wireless ad-hoc networks (WANETs). The researches in WANETs have attracted significant attentions, and one of the most critical issues in WSNs is minimization of energy consumption. In WANETs the packets have to be transported from a given source node to all other nodes in the network, and the objective of the MEB problem is to minimize the total transmission power consumption. A hybrid algorithm based on particle swarm optimization (PSO) and local search is presented to solve the MEB problem. A power degree encoding is proposed to reflect the extent of transmission power level and is used to define the particle position in PSO. We also analyze a well-known local search mechanism, r-shrink, and propose an improved version, the intensified r-shrink. In order to solve the dynamic MEB problem with node removal/insertion, this paper provides an effective simple heuristic, Conditional Incremental Power (CIP), to reconstruct the broadcast network efficiently. The promising results indicate the potential of the proposed methods for practical use.

Research paper thumbnail of Flexible Job Shop Scheduling Using a Multiobjective Memetic Algorithm

This paper addresses the flexible job shop scheduling problem with minimization of the makespan, ... more This paper addresses the flexible job shop scheduling problem with minimization of the makespan, maximum machine workload, and total machine workload as the objectives. A multiobjective memetic algorithm is proposed. It belongs to the integrated approach, which deals with the routing and sequencing sub-problems together. Dominance-based and aggregation-based fitness assignment methods are used in the parts of genetic algorithm and local search, respectively. The local search procedure follows the framework of variable neighborhood descent algorithm. The proposed algorithm is compared with three benchmark algorithms using fifteen classic problem instances. Its performance is better in terms of the number and quality of the obtained solutions.