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Mathematical model and simulated annealing algorithm for Chinese high school timetabling problems under the new curriculum innovation 被引量:1
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作者 Xingxing HAO Jing LIU +1 位作者 Yutong ZHANG Gustaph SANGA 《Frontiers of Computer Science》 SCIE EI CSCD 2021年第1期167-177,共11页
As the first attempt,this paper proposes a model for the Chinese high school timetabling problems(CHSTPs)under the new curriculum innovation which was launched in 2011 by the Chine6e government.Aooording 10 the new ou... As the first attempt,this paper proposes a model for the Chinese high school timetabling problems(CHSTPs)under the new curriculum innovation which was launched in 2011 by the Chine6e government.Aooording 10 the new our riculum innovation,students in high school can choose subjects that they are interested in instead of being forced to select one of the two study directions,namely,Science and Liberal Arts.Meanwhile,they also need to attend compulsory subjects as traditions.CHSTPs are student-oriented and involve more student constraints that make them more complex than the typi-cal"Class-Teacher model",in which the element"Teacher"is the primary constraint.In this paper,we first describe in detail the mathematical model of CHSTPs and then design a new two-part representation for the candidate solution.Based on the new representation,we adopt a two-phase simulated annealing(SA)algorithm to solve CHSTPs.A total number of 45 synthetic instances with different amounts of classes,teachers,and levels of student constraints are generated and used to ilustrate the characteristics of the CHSTP model and the effectiveness of the designed representation and algorithm.Finally,we apply the proposed model,the designed two-part representation and the two-phase SA on10 real high schools. 展开更多
关键词 timetabling Chinese high school timetabling problem simulated annealing two-part representation
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A memetic algorithm based on hyper-heuristics for examination timetabling problems
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作者 Yu Lei Maoguo Gong +1 位作者 Licheng Jiao Yi Zuo 《International Journal of Intelligent Computing and Cybernetics》 EI 2015年第2期139-151,共13页
Purpose–The examination timetabling problem is an NP-hard problem.A large number of approaches for this problem are developed to find more appropriate search strategies.Hyper-heuristic is a kind of representative met... Purpose–The examination timetabling problem is an NP-hard problem.A large number of approaches for this problem are developed to find more appropriate search strategies.Hyper-heuristic is a kind of representative methods.In hyper-heuristic,the high-level search is executed to construct heuristic lists by traditional methods(such as Tabu search,variable neighborhoods and so on).The purpose of this paper is to apply the evolutionary strategy instead of traditional methods for high-level search to improve the capability of global search.Design/methodology/approach–This paper combines hyper-heuristic with evolutionary strategy to solve examination timetabling problems.First,four graph coloring heuristics are employed to construct heuristic lists.Within the evolutionary algorithm framework,the iterative initialization is utilized to improve the number of feasible solutions in the population;meanwhile,the crossover and mutation operators are applied to find potential heuristic lists in the heuristic space(high-level search).At last,two local search methods are combined to optimize the feasible solutions in the solution space(low-level search).Findings–Experimental results demonstrate that the proposed approach obtains competitive results and outperforms the compared approaches on some benchmark instances.Originality/value–The contribution of this paper is the development of a framework which combines evolutionary algorithm and hyper-heuristic for examination timetabling problems. 展开更多
关键词 Evolutionary computation Examination timetabling problem Hyper-heuristic Memetic algorithm
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A simulation-based optimization approach for passenger train timetabling with periodic track maintenance and stops for praying
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作者 Zahra Bahramian Morteza Bagheri 《Journal of Modern Transportation》 2015年第2期148-157,共10页
This paper presents two optimization methods for solving the passenger train timetabling problem to minimize the total delay time in the single track railway networks. The goal of the train timetable problem is to det... This paper presents two optimization methods for solving the passenger train timetabling problem to minimize the total delay time in the single track railway networks. The goal of the train timetable problem is to determine departure and arrival times to or from each station in order to prevent collisions between trains and effective utilization of resources. The two proposed methods are based on integration of a simulation and an optimization method to simulate train traffic flow and generate near optimal train timetable under realistic con- straints including stops for track maintenance and praying. The first proposed method integrates a cellular automata (CA) simulation model with genetic algorithm optimiza- tion method. In the second proposed approach, a CA simulation model combines with dynamically dimensioned search optimization method. The proposed models are applied to hypothetical case study to demonstrate the merit of them. The Islamic Republic of Iran Railways (IRIR) data and regulations have been used to optimize train timetable. The results show the first method is more effi- cient than the second method to obtain near optimal train timetabling. 展开更多
关键词 Train timetabling problem (TTP) Cellularautomata (CA) Genetic algorithm (GA) Dynamicallydimensioned search (DDS) algorithm STATION Trackmaintenance PRAYING
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A Multiple-Neighborhood-Based Parallel Composite Local Search Algorithm for Timetable Problem
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作者 颜鹤 郁松年 《Journal of Shanghai University(English Edition)》 CAS 2004年第3期301-308,共8页
This paper presents a parallel composite local search algorithm based on multiple search neighborhoods to solve a special kind of timetable problem. The new algorithm can also effectively solve those problems that can... This paper presents a parallel composite local search algorithm based on multiple search neighborhoods to solve a special kind of timetable problem. The new algorithm can also effectively solve those problems that can be solved by general local search algorithms. Experimental results show that the new algorithm can generate better solutions than general local search algorithms. 展开更多
关键词 multiple neighborhoods PARALLEL composite local search algorithm timetable problem.
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