Kód: 07165112
Most real world problems require the simultaneous optimization of multiple, competing, criteria (or objectives). In this case, the aim of a multiobjective resolution approach is to find a number of solutions known as Paretooptimal ... celý popis
Angličtina
35.74 €
Bežne: 41.88 €
Ušetríte 6.14 €

Nákupom získate 86 bodov
Anotácia knihy
Most real world problems require the simultaneous optimization of multiple, competing, criteria (or objectives). In this case, the aim of a multiobjective resolution approach is to find a number of solutions known as Paretooptimal solutions. Evolutionary algorithms manipulate a population of solutions and thus are suitable to solve multi-objective optimization problems. In addition parallel evolutionary algorithms aim at reducing the computation time and solving large combinatorial optimization problems. In this work we study the performance of the Balanced Explore Exploit Distributed Evolutionary Algorithm (BEEDEA) [1] on the multi-objective Knapsack problem which is a combinatorial optimization problem. BEEDA is implemented after some improvements and tested on the Knapsack problem. Key words: multi-objective optimization, evolutionary algorithms, Knapsack problem, distributed metaheuristics.
Parametre knihy
Zaradenie knihy Knihy po anglicky Literature & literary studies Literature: history & criticism Literary studies: general
35.74 €
Angličtina
Osobný odber Bratislava a 12840 dalších
Copyright ©2008-26 najlacnejsie-knihy.sk Všetky práva vyhradenéSúkromieCookies
24 miliónov titulov
Vrátenie do mesiaca
02/210 210 99 (8-15.30h)Nákupný košík ( prázdny )