처리시간의 합 기반 에이징 효과를 갖는 tardiness를 고려한 단일기계 two 에이전트 스케줄링

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dc.contributor.advisor최진영-
dc.contributor.author김도균-
dc.date.accessioned2018-11-08T08:20:54Z-
dc.date.available2018-11-08T08:20:54Z-
dc.date.issued2015-02-
dc.identifier.other19347-
dc.identifier.urihttps://dspace.ajou.ac.kr/handle/2018.oak/12868-
dc.description학위논문(석사)--아주대학교 일반대학원 :산업공학과,2015. 2-
dc.description.abstractIn recent studies of scheduling, a multi-agent scheduling problem has been recognized as an important issue, where multiple decision makers perform scheduling while considering their own objectives and competing for resources. Limited scheduling resources can be efficiently utilized by a suitable solution for the multi agent scheduling problem. Meanwhile, there is another element that should be considered, namely learning and aging effect. The actual processing time in real industry can be increased or decreased by them. In recent years, multi-agent scheduling and learning/aging effect are considered simultaneously. However, they did not consider the due date. Although the due date is as important as cost, there are few studies considering the due date because of its high computational complexity. Motivated by these remarks, we consider a single-machine two-agent scheduling problem with the aging effect based on sum-of-processing-times, where one agent wants to minimize total weighted tardiness, not allowing tardy job for the other agent. We develop a branch-and-bound (B&B) algorithm and a genetic algorithm (GA). We propose dominance properties and lower bound for an efficient B&B algorithm and consider four initial populations to improve the performance of the GA. We implemented the suggested algorithms using MATLAB and performed a numerical experiment to show the superiority of them.-
dc.description.tableofcontentsTable of Contents Acknowledgement i Abstract ii List of tables v List of figures vi Chapter 1. Introduction 1 1.1 Purpose and need for research 1 1.2 Previous studies and approaches 4 1.3 Organization of thesis 8 Chapter 2. Problem definition and branch-and-bound algorithm 9 2.1 Problem definition 9 2.2 Branch-and-bound algorithm 13 Chapter 3. Genetic algorithm 22 3.1 Representation of chromosome 23 3.2 Initial population 23 3.3 Fitness function 24 3.4 Crossover operation 24 3.5 Mutation 26 3.6 Population update and termination criteria 27 Chapter 4. Numerical experiment 29 4.1 Experimental design 29 4.2 Analysis of experimental results 31 Chapter 5. Conclusion 38 Bibliography 40 Appendix A. MATLAB Code for proposed B&B algorithm and GA 46 List of tables Table 1. A scheduling example to calculate lower bound 21 Table 2. Experimental results of B&B and GA 32 Table 3. Results of paired T-test between two GAs 36 List of figures Figure 1. The concept of multi-agent scheduling 1 Figure 2. Complexity hierarchies of scheduling problems 4 Figure 3. Two schedules and including two adjacent jobs and 14 Figure 4. The procedure of genetic algorithm 22 Figure 5. Representation of chromosome using permutation encoding 23 Figure 6. Examples of crossover operator 25 Figure 7. Range of due dates generated by two and three parameters 30-
dc.language.isoeng-
dc.publisherThe Graduate School, Ajou University-
dc.rights아주대학교 논문은 저작권에 의해 보호받습니다.-
dc.title처리시간의 합 기반 에이징 효과를 갖는 tardiness를 고려한 단일기계 two 에이전트 스케줄링-
dc.typeThesis-
dc.contributor.affiliation아주대학교 일반대학원-
dc.contributor.department일반대학원 산업공학과-
dc.date.awarded2015. 2-
dc.description.degreeMaster-
dc.identifier.localId695693-
dc.identifier.urlhttp://dcoll.ajou.ac.kr:9080/dcollection/jsp/common/DcLoOrgPer.jsp?sItemId=000000019347-
dc.subject.keyword단일기계-
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Special Graduate Schools > Graduate School of Science and Technology > Department of Industrial Engineering > 3. Theses(Master)
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