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2007 IEEE Symposium on Computational Intelligence in Scheduling最新文献

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A Discrete Differential Evolution Algorithm for the No-Wait Flowshop Scheduling Problem with Total Flowtime Criterion 无等待流水车间调度问题的离散差分进化算法
2007 IEEE Symposium on Computational Intelligence in Scheduling Pub Date : 2007-04-01 DOI: 10.1109/SCIS.2007.367698
M. Tasgetiren, Q. Pan, P. N. Suganthan, Yun-Chia Liang
{"title":"A Discrete Differential Evolution Algorithm for the No-Wait Flowshop Scheduling Problem with Total Flowtime Criterion","authors":"M. Tasgetiren, Q. Pan, P. N. Suganthan, Yun-Chia Liang","doi":"10.1109/SCIS.2007.367698","DOIUrl":"https://doi.org/10.1109/SCIS.2007.367698","url":null,"abstract":"In this paper, a discrete differential evolution (DDE) algorithm is presented to solve the no-wait flowshop scheduling problem with the total flowtime criterion. The DDE algorithm is hybridized with the variable neighborhood descent (VND) algorithm to solve the well-known benchmark suites in the literature. The DDE algorithm is applied to the 110 benchmark instances of Taillard (1993) by treating them as the no-wait flowshop problem instances with the total flowtime criterion. The solution quality is evaluated with optimal solutions, lower bounds and best known solutions provided by Fink & Voss (2003). The computational results show that the DDE algorithm generated better results than those in Fink & Voss (2003).","PeriodicalId":184726,"journal":{"name":"2007 IEEE Symposium on Computational Intelligence in Scheduling","volume":"108 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115876122","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 54
Static Task Scheduling Using Genetic Algorithm and Reinforcement Learning 基于遗传算法和强化学习的静态任务调度
2007 IEEE Symposium on Computational Intelligence in Scheduling Pub Date : 2007-04-01 DOI: 10.1109/SCIS.2007.367694
Mohammad Moghimi Najafabadi, Mustafa Zali, S. Taheri, F. Taghiyareh
{"title":"Static Task Scheduling Using Genetic Algorithm and Reinforcement Learning","authors":"Mohammad Moghimi Najafabadi, Mustafa Zali, S. Taheri, F. Taghiyareh","doi":"10.1109/SCIS.2007.367694","DOIUrl":"https://doi.org/10.1109/SCIS.2007.367694","url":null,"abstract":"Task scheduling in a multiprocessor system is defined as assigning a set of tasks to a set of processors. The goal is to minimize the execution time while meeting a set of constraints. A wide variety set of deterministic and heuristic methods are proposed to solve the problem. The main problem is that the proposed methods cannot deal with big search spaces and cannot guarantee to find the optimal solution. In this research a novel approach based on reinforcement learning and genetic algorithm is proposed. Being divided using genetic algorithm, the smaller problems can be solved with reinforcement learner scheduler. The result of the method is a set of task processor pairs. Simulation results in standard problem set show that the method outperforms some studied GA based scheduling methods","PeriodicalId":184726,"journal":{"name":"2007 IEEE Symposium on Computational Intelligence in Scheduling","volume":"347 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122756137","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 1
Test Machine Scheduling and Optimization for z/ OS z/ OS测试机调度与优化
2007 IEEE Symposium on Computational Intelligence in Scheduling Pub Date : 2007-04-01 DOI: 10.1109/SCIS.2007.367666
M. Kaplan, T. Kimbrel, Kevin Mckenzie, R. Prewitt, M. Sviridenko, Clay E. Williams, Cemal Yilmaz
{"title":"Test Machine Scheduling and Optimization for z/ OS","authors":"M. Kaplan, T. Kimbrel, Kevin Mckenzie, R. Prewitt, M. Sviridenko, Clay E. Williams, Cemal Yilmaz","doi":"10.1109/SCIS.2007.367666","DOIUrl":"https://doi.org/10.1109/SCIS.2007.367666","url":null,"abstract":"We describe a system for solving a complex scheduling problem faced by software product test organizations. Software testers need time on test machines with specific features and configurations to perform the test tasks assigned to them. There is a limited number of machines with any given configuration, and this makes the machines scarce resources. Deadlines are always short. Thus, testers must reserve time on machines. Managing a schedule for a large test organization is a difficult task to perform manually. Requirements change frequently, making the task even more onerous, yet scheduling is done by hand in most teams. Our scheduling system is able to take into account the many and varied constraints and preferences that a team of human users inevitably has","PeriodicalId":184726,"journal":{"name":"2007 IEEE Symposium on Computational Intelligence in Scheduling","volume":"95 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116716548","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
A Robust Method for the VRPTW with Multi-Start Simulated Annealing and Statistical Analysis 基于多启动模拟退火和统计分析的VRPTW鲁棒方法
2007 IEEE Symposium on Computational Intelligence in Scheduling Pub Date : 2007-04-01 DOI: 10.1109/SCIS.2007.367690
Humberto Cesar Brandao de Oliveira, G. C. Vasconcelos, G. B. Alvarenga, R. V. Mesquita, Mariane Moreira de Souza
{"title":"A Robust Method for the VRPTW with Multi-Start Simulated Annealing and Statistical Analysis","authors":"Humberto Cesar Brandao de Oliveira, G. C. Vasconcelos, G. B. Alvarenga, R. V. Mesquita, Mariane Moreira de Souza","doi":"10.1109/SCIS.2007.367690","DOIUrl":"https://doi.org/10.1109/SCIS.2007.367690","url":null,"abstract":"Vehicle routing problems have been extensively analyzed to reduce transportation costs. More particularly, the vehicle routing problem with time windows (VRPTW) imposes the period of time of customer availability as a constraint, a very common characteristic in real world situations. Using minimization of the total distance as the main objective to be fulfilled, this work implements an efficient hybrid system which associates non-monotonic simulated annealing to hill climbing with random restart (multi-start). Firstly, the algorithm is compared to the best results published in the literature for the 56 Solomon instances. Then, it is shown how statistical methods - analysis of variance and linear regression - can be used to determine the significance degree of the system's parameters to obtain an even better and more reliable performance","PeriodicalId":184726,"journal":{"name":"2007 IEEE Symposium on Computational Intelligence in Scheduling","volume":"32 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116961136","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 14
Memory Length in Hyper-heuristics: An Empirical Study 超启发式记忆长度的实证研究
2007 IEEE Symposium on Computational Intelligence in Scheduling Pub Date : 2007-04-01 DOI: 10.1109/SCIS.2007.367686
Ruibin Bai, E. Burke, M. Gendreau, G. Kendall, B. McCollum
{"title":"Memory Length in Hyper-heuristics: An Empirical Study","authors":"Ruibin Bai, E. Burke, M. Gendreau, G. Kendall, B. McCollum","doi":"10.1109/SCIS.2007.367686","DOIUrl":"https://doi.org/10.1109/SCIS.2007.367686","url":null,"abstract":"Hyper-heuristics are an emergent optimisation methodology which aims to give a higher level of flexibility and domain-independence than is currently possible. Hyper-heuristics are able to adapt to the different problems or problem instances by dynamically choosing between heuristics during the search. This paper is concerned with the issues of memory length on the performance of hyper-heuristics. We focus on a recently proposed simulated annealing hyper-heuristic and choose a set of hard university course timetabling problems as the test bed for this empirical study. The experimental results show that the memory length can affect the performance of hyper-heuristics and a good choice of memory length is able to improve solution quality. Finally, two dynamic approaches are investigated and one of the approaches is shown to be able to produce promising results without introducing extra sensitive algorithmic parameters.","PeriodicalId":184726,"journal":{"name":"2007 IEEE Symposium on Computational Intelligence in Scheduling","volume":"79 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115157159","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 30
Scaling Adaptive Agent-Based Reactive Job-Shop Scheduling to Large-Scale Problems 大规模问题的自适应agent响应式作业车间调度
2007 IEEE Symposium on Computational Intelligence in Scheduling Pub Date : 2007-04-01 DOI: 10.1109/SCIS.2007.367699
T. Gabel, Martin A. Riedmiller
{"title":"Scaling Adaptive Agent-Based Reactive Job-Shop Scheduling to Large-Scale Problems","authors":"T. Gabel, Martin A. Riedmiller","doi":"10.1109/SCIS.2007.367699","DOIUrl":"https://doi.org/10.1109/SCIS.2007.367699","url":null,"abstract":"Most approaches to tackle job-shop scheduling problems assume complete task knowledge and search for a centralized solution. In this work, we adopt an alternative view on scheduling problems where each resource is equipped with an adaptive agent that, independent of other agents, makes job dispatching decisions based on its local view on the plant and employs reinforcement learning to improve its dispatching strategy. We delineate which extensions are necessary to render this learning approach applicable to job-shop scheduling problems of current standards of difficulty and present results of an adequate empirical evaluation","PeriodicalId":184726,"journal":{"name":"2007 IEEE Symposium on Computational Intelligence in Scheduling","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130256611","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 21
A new meta-heuristic for the Bus Driver Scheduling Problem: GRASP combined with Rollout 求解公交司机调度问题的一种新的元启发式算法:GRASP与Rollout相结合
2007 IEEE Symposium on Computational Intelligence in Scheduling Pub Date : 2007-04-01 DOI: 10.1109/SCIS.2007.367689
Gionatan D'Annibale, R. Leone, P. Festa, E. Marchitto
{"title":"A new meta-heuristic for the Bus Driver Scheduling Problem: GRASP combined with Rollout","authors":"Gionatan D'Annibale, R. Leone, P. Festa, E. Marchitto","doi":"10.1109/SCIS.2007.367689","DOIUrl":"https://doi.org/10.1109/SCIS.2007.367689","url":null,"abstract":"The bus driver scheduling problem (BDSP) is one of the most important planning decision problems that public transportation companies must solve and that appear as an extremely complex part of the general transportation planning system. It is formulated as a minimization problem whose objective is to determine the minimum number of driver shifts, subject to a variety of rules and regulations that must be enforced, such as overspread and working time. In this article, a greedy randomized adaptive search procedure (GRASP) and a rollout heuristic for BDSP are proposed and tested. A new hybrid heuristic that combines GRASP and rollout is also proposed and tested. Computational results indicate that these randomized heuristics find near-optimal solutions","PeriodicalId":184726,"journal":{"name":"2007 IEEE Symposium on Computational Intelligence in Scheduling","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122229840","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 12
Solving the Exam Timetabling Problem via a Multi-Objective Evolutionary Algorithm - A More General Approach 用多目标进化算法解决考试排课问题——一种更通用的方法
2007 IEEE Symposium on Computational Intelligence in Scheduling Pub Date : 2007-04-01 DOI: 10.1109/SCIS.2007.367685
C. Cheong, K. Tan, B. Veeravalli
{"title":"Solving the Exam Timetabling Problem via a Multi-Objective Evolutionary Algorithm - A More General Approach","authors":"C. Cheong, K. Tan, B. Veeravalli","doi":"10.1109/SCIS.2007.367685","DOIUrl":"https://doi.org/10.1109/SCIS.2007.367685","url":null,"abstract":"This paper studies a multi-objective instance of the university exam timetabling problem. On top of satisfying universal hard constraints such as seating capacity and no overlapping exams, the solution to this problem requires the minimization of the timetable length as well as the number of occurrences of students having to take exams in consecutive periods within the same day. While most existing approaches to the problem, as well as the more popular single-objective instance, require prior knowledge of the desired timetable length, the multi-objective evolutionary algorithm proposed in this paper is able to generate feasible solutions even without the information. The effectiveness of the proposed algorithm is benchmarked against a few recent and established optimization techniques and is found to perform well in comparison","PeriodicalId":184726,"journal":{"name":"2007 IEEE Symposium on Computational Intelligence in Scheduling","volume":"17 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129003320","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 21
Solving Dynamic Single-Runway Aircraft Landing Problems With Extremal Optimisation 基于极限优化的单跑道飞机动态着陆问题求解
2007 IEEE Symposium on Computational Intelligence in Scheduling Pub Date : 2007-04-01 DOI: 10.1109/SCIS.2007.367691
I. Moser, T. Hendtlass
{"title":"Solving Dynamic Single-Runway Aircraft Landing Problems With Extremal Optimisation","authors":"I. Moser, T. Hendtlass","doi":"10.1109/SCIS.2007.367691","DOIUrl":"https://doi.org/10.1109/SCIS.2007.367691","url":null,"abstract":"A dynamic implementation of the single-runway aircraft landing problem was chosen for experiments designed to investigate the adaptive capabilities of extremal optimisation. As part of the problem space is unimodal, we developed a deterministic algorithm which optimises the time lines of the permutations found by the EO solver. To assess our results, we experimented on known problem instances for which benchmark solutions exist. The nature and difficulty of the instances used were assessed to discuss the quality of results obtained by the solver. Compared to the benchmark results available, our approach was highly competitive","PeriodicalId":184726,"journal":{"name":"2007 IEEE Symposium on Computational Intelligence in Scheduling","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126643423","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 28
A Genetic Algorithm for Scheduling Parallel Non-identical Batch Processing Machines 并行非同构批处理机器调度的遗传算法
2007 IEEE Symposium on Computational Intelligence in Scheduling Pub Date : 2007-04-01 DOI: 10.1109/SCIS.2007.367682
Shubin Xu, J. C. Bean
{"title":"A Genetic Algorithm for Scheduling Parallel Non-identical Batch Processing Machines","authors":"Shubin Xu, J. C. Bean","doi":"10.1109/SCIS.2007.367682","DOIUrl":"https://doi.org/10.1109/SCIS.2007.367682","url":null,"abstract":"In this paper, we study the scheduling problem of minimizing makespan on parallel non-identical batch processing machines. We formulate the scheduling problem into an integer programming model. Due to the difficulty of the problem, it is hard to solve the problem with standard mathematical programming software. We propose a genetic algorithm based on random keys encoding to address this problem. Computational results show that this genetic algorithm consistently finds a solution in a reasonable amount of computation time","PeriodicalId":184726,"journal":{"name":"2007 IEEE Symposium on Computational Intelligence in Scheduling","volume":"35 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133244022","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 55
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