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Titlebook: Evolutionary Computation in Combinatorial Optimization; 17th European Confer Bin Hu,Manuel López-Ibáñez Conference proceedings 2017 Springe

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发表于 2025-3-21 16:05:12 | 显示全部楼层 |阅读模式
书目名称Evolutionary Computation in Combinatorial Optimization
副标题17th European Confer
编辑Bin Hu,Manuel López-Ibáñez
视频video
概述Includes supplementary material:
丛书名称Lecture Notes in Computer Science
图书封面Titlebook: Evolutionary Computation in Combinatorial Optimization; 17th European Confer Bin Hu,Manuel López-Ibáñez Conference proceedings 2017 Springe
描述This book constitutes the refereed proceedings of the 17th European Conference on Evolutionary Computation in Combinatorial Optimization, EvoCOP 2017, held in Amsterdam, The Netherlands, in April 2017, co-located with the Evo*2017 events EuroGP, EvoMUSART and EvoApplications..The 16 revised full papers presented were carefully reviewed and selected from 39 submissions. The papers cover both empirical and theoretical studies on a wide range of academic and real-world applications. The methods include evolutionary and memetic algorithms, large neighborhood search, estimation of distribution algorithms, beam search, ant colony optimization, hyper-heuristics and matheuristics. Applications include both traditional domains, such as knapsack problem, vehicle routing, scheduling problems and SAT; and newer domains such as the traveling thief problem, location planning for car-sharing systems and spacecraft trajectory optimization. Papers also study important concepts such as pseudo-backbones, phase transitions in local optima networks, and the analysis of operators. This wide range of topics makes the EvoCOP proceedings an important source for current research trends in combinatorial opti
出版日期Conference proceedings 2017
关键词combinatorial optimization; discrete space search; evolutionary algorithms; metaheuristics; particle swa
版次1
doihttps://doi.org/10.1007/978-3-319-55453-2
isbn_softcover978-3-319-55452-5
isbn_ebook978-3-319-55453-2Series ISSN 0302-9743 Series E-ISSN 1611-3349
issn_series 0302-9743
copyrightSpringer International Publishing AG 2017
The information of publication is updating

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发表于 2025-3-21 23:15:28 | 显示全部楼层
A Genetic Algorithm for Multi-component Optimization Problems: The Case of the Travelling Thief Pronce are not a good choice to assess algorithm performance. In recent literature, a benchmark problem called Travelling Thief Problem (TTP) was proposed to better represent real-world multi-component problems. TTP is a combination of two well-known problems: 0-1 Knapsack Problem (KP) and the Travelli
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A Memetic Algorithm to Maximise the Employee Substitutability in Personnel Shift Scheduling,ions usually operate in a stochastic environment and are confronted with unexpected events in the short term. These unexpected events affect the workability of the personnel roster and need to be resolved efficiently and effectively. To facilitate this short-term recovery, it is important to conside
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LCS-Based Selective Route Exchange Crossover for the Pickup and Delivery Problem with Time Windows, of homogeneous trucks. Its main objective is to minimize the number of vehicles, and the secondary objective is to minimize the distance traveled during the service. In this paper, we propose the longest common subsequence based selective route exchange crossover (LCS-SREX), and apply this operator
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