Titlebook: Evolutionary Computation in Combinatorial Optimization; 11th European Confer Peter Merz,Jin-Kao Hao Conference proceedings 2011 Springer Be

粗略

书目名称Evolutionary Computation in Combinatorial Optimization影响因子(影响力)




书目名称Evolutionary Computation in Combinatorial Optimization影响因子(影响力)学科排名




书目名称Evolutionary Computation in Combinatorial Optimization网络公开度




书目名称Evolutionary Computation in Combinatorial Optimization网络公开度学科排名




书目名称Evolutionary Computation in Combinatorial Optimization被引频次




书目名称Evolutionary Computation in Combinatorial Optimization被引频次学科排名




书目名称Evolutionary Computation in Combinatorial Optimization年度引用




书目名称Evolutionary Computation in Combinatorial Optimization年度引用学科排名




书目名称Evolutionary Computation in Combinatorial Optimization读者反馈




书目名称Evolutionary Computation in Combinatorial Optimization读者反馈学科排名

共同时代

Roberto Cavallo Perin,Gabriella M. Raccaution. Different diversification strategies and feasibility search rules are proposed. We present computational results on a wide set of instances up to 50 customers and 5 satellites and compare them with results from the literature, showing how the new methods outperform previous existent methods,

畸形

Multi-start Heuristics for the Two-Echelon Vehicle Routing Problem,ution. Different diversification strategies and feasibility search rules are proposed. We present computational results on a wide set of instances up to 50 customers and 5 satellites and compare them with results from the literature, showing how the new methods outperform previous existent methods,

aneurysm

Evolutionary Computation in Combinatorial Optimization11th European Confer

两栖动物

白杨

白杨

https://doi.org/10.1057/9780333981733metabling problem (MOUCTP) and proposes a guided search non-dominated sorting genetic algorithm to solve the MOUCTP. The proposed algorithm integrates a guided search technique, which uses a memory to store useful information extracted from previous good solutions to guide the generation of new solu

CHIP

Documentation and Bibliography, objective of minimizing the maximum lateness. We developed a hybrid dual-population genetic algorithm and compared its performance with alternative methods on a new diverse data set. Extensions from a single to a dual population by taking problem specific characteristics into account can be seen as

相信

该得

https://doi.org/10.1007/978-94-009-7371-8ective function value with respect to the solutions provided by state of the art procedures. The proposed procedure is based on the positional completion times integer programming formulation of the problem with .(..) variables and .(.) constraints.