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研究生: 潘英發
Frans - Januar Panto
論文名稱: A job-shop scheduling algorithm based on hybrid bees algorithm combined with tabu search
A job-shop scheduling algorithm based on hybrid bees algorithm combined with tabu search
指導教授: 洪西進
Shi-Jinn Horng
口試委員: 邱舉明
none
金台齡
none
項天瑞
none
學位類別: 碩士
Master
系所名稱: 電資學院 - 資訊工程系
Department of Computer Science and Information Engineering
論文出版年: 2010
畢業學年度: 98
語文別: 英文
論文頁數: 39
中文關鍵詞: Job-shop scheduling problem (JSSP)Bees Algorithm (BA)Tabu Search (TS)Neighborhood Structure (NS)
外文關鍵詞: Job-shop scheduling problem (JSSP), Bees Algorithm (BA), Tabu Search (TS), Neighborhood Structure (NS)
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The job-shop scheduling problem is one of the most NP-Hard problems and has attracted many researchers to develop new algorithm based on heuristic or meta-heuristic approach. Many algorithms based on Genetic Algorithm, Particle Swarm Optimization, Ant Colony Optimization have been proposed to solve it, respectively but the results are still not yet satisfactory. In this paper we proposed a new algorithm based on bees algorithm which is very good for discrete optimization problem; furthermore, the results are optimized with the famous tabu search for local search to improve the results. The robustness, efficiency, and effectiveness of this algorithm are examined using a set of benchmark instances and compared with existing algorithms. The results show that the proposed algorithm could obtain competitive results within reasonable computing times.


The job-shop scheduling problem is one of the most NP-Hard problems and has attracted many researchers to develop new algorithm based on heuristic or meta-heuristic approach. Many algorithms based on Genetic Algorithm, Particle Swarm Optimization, Ant Colony Optimization have been proposed to solve it, respectively but the results are still not yet satisfactory. In this paper we proposed a new algorithm based on bees algorithm which is very good for discrete optimization problem; furthermore, the results are optimized with the famous tabu search for local search to improve the results. The robustness, efficiency, and effectiveness of this algorithm are examined using a set of benchmark instances and compared with existing algorithms. The results show that the proposed algorithm could obtain competitive results within reasonable computing times.

ABSTRACTi ACKNOWLEDGMENTSii CONTENTS iii LIST OF ALGORITHMSiv LIST OF FIGURES v LIST OF TABLESvi Chapter 1. INTRODUCTION 1 1.1. Motivation 1 1.2. Research objectives 2 1.3. Organization of thesis 3 Chapter 2. PRELIMINARIES 4 2.1. Job shop scheduling problem 4 2.2. Bees algorithm 7 2.2.1. The idea of bees algorithm 7 2.2.2 Bees algorithm 8 Chapter 3. PROPOSED ALGORITHMS 10 3.1. Representation of bees 10 3.2. Neighborhood structure 11 3.3. Critical path based crossover 12 3.4. Local search 16 3.5. The HBTS algorithm 16 Chapter 4. EXPERIMENTAL RESULTS 23 4.1. Computational results 23 4.2. User interface 26 Chapter 5. CONCLUSIONS 27 5.1. Conclusions 27 5.2. Future studies 27 REFERENCES 28

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