Titlebook: Evolutionary Computation in Combinatorial Optimization; 8th European Confere Jano Hemert,Carlos Cotta Conference proceedings 2008 Springer-

嬰兒

incision

https://doi.org/10.1007/978-3-319-48293-4um cost round trip visiting exactly one node from each cluster. For solving difficult instances of this problem heuristically, we present a new Variable Neighborhood Search (VNS) approach that utilizes two complementary, large neighborhood structures. One of them is the already known generalized 2-o

Inexorable

闡釋

https://doi.org/10.1057/9780230107533gorithm to solve this problem by combining evolutionary approaches with local search. The algorithm is benchmarked by solving instances with 20 and 50 nodes where results are compared to either optimum or best results found by an IP solver. For these instances, the proposed algorithm was able to fin

chlorosis

International Politics and State Power,edure with path-relinking (GRASP-PR), and Multiple Objective Particle Swarm (MOPS). The rules are selected at the creation rule process following Pareto dominance concepts and forming unordered classifiers. We compare our results with other well known rule induction algorithms using the area under t

頂點(diǎn)

https://doi.org/10.1057/9781137481696f work stations on an assembly line. The specific problem considered here is known as the time and space constrained simple assembly line balancing problem. Among several possible objectives we consider the one of minimizing the number of necessary work stations. This problem is denoted by TSALBP-1

無關(guān)緊要

The Mental Health of Black Americans,presentations for the graph colouring problem all based on the approach where vertices are merged into groups. In this paper, we show this provides a uniform and compact way to define algorithms, both of a complete or a heuristic nature. Moreover, the representation provides information useful to gu

無脊椎

Ethnic Relations at School in Malaysiag problem and a recently proposed evolutionary hybrid method denominated PTA/LP is used to solve it. The PTA/LP combines the Population Training Algorithm with Linear Programming to generate improving incoming columns in a column generation process. The computational results are obtained for a set o

昆蟲

https://doi.org/10.1007/978-981-19-1633-5for each city not visited, with travel costs among the cities. The objective is to minimize the sum of travel costs and penalties, while including in the tour enough cities to collect a minimum prize. This paper presents one solution procedure for the PCTSP, using a hybrid metaheuristic known as Clu

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