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A heuristic algorithm for cube packing with time schedule

Science China(Information Sciences) 2010年第1期53卷 18-29页

作者： LI Wei1, HUANG WenQi2, JIANG DongChen1 & LIU XiangLong1 1State Key Laboratory of Software Development Environment, Beihang University, Beijing 100191, China 2School of Computer Science and Technology, Huazhong University of Science and Technology, Wuhan 430074, China State Key Laboratory of Software Development Environment Beihang University School of Computer Science and Technology Huazhong University of Science and Technology

Packing problem has been proved to be an NP-hard problem. Many algorithms such as simulation annealing algorithm, genetic algorithm and other heuristic algorithms have been proposed to solve twodimensional and three-dimensional packing problem. To solve the cube packing problem with time schedule, this paper first introduces some concepts such as packing level, space distance and average neighbor birth order and then proposes a greedy algorithm. The algorithm tries every feasible corner greedily to calculate the space utilization, packing level, space distance, average neighbor birth order of this placement, and chooses the best placement according to these criteria. Theoretical analysis indicates that the time complexity of this algorithm is O(A2B2C2T 2n5). The experiments show that the average space utilization of non-guillotine cutting test cases is 98.81%, and the average space utilization of guillotine cutting test cases achieves 99.87%. Furthermore, optimal solutions of more than half cases are achieved by this algorithm. The experimental results show that this algorithm can solve the problem of cube packing with time schedule effectively and effciently.

关键词： cube packing problem time schedule packing level space distance average neighbor birth order

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Enhancement of SA Algorithm by Intelligent time schedule

Enhancement of SA Algorithm by Intelligent Time Schedule

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第二十九届中国控制会议

作者： K.Shojaee G. M.Behnam T. H.Shakouri G. M.Rezaei Dep.of Electrical and Computer Eng. University of Tehran Mechatronics Laboratory(LIM) Politecnico di Torino Dep.of Industrial Engineering University of Tehran Dep.of Mechanical&Aerospace Eng. Science&Research Branch Islamic Azad University

In this paper we present a glancing review of how to define the time schedule of Simulated Annealing（SA） algorithm in different articles that applied them to solve the traveling salesman problem（TSP）.In the following subjects we introduce a new definition of this concept in relation to other *** other word,we claim a novel description of initial temperature,Markov chain and final temperature to the basic algorithm of SA that gives an introduction to New time schedule Simulated Annealing（NTSSA）.In this method,the dynamic coincidence of time schedule parameters and temperature conditions is a possible happening among the searching *** continuation we present the obtaining results of proposed algorithm in solving TSP in comparison with basic methods of SA and other intelligent optimization *** surprising improvement in results obtained by this approach shows the efficiency of NTSSA in contrast with other basic optimization methods.

关键词： Combinatorial Optimization Traveling Salesman Problems Simulated Annealing time schedule

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