Beedea's Performance on Knapsack Problem

Name: Beedea's Performance on Knapsack Problem
Brand: Omniscriptum
SKU: 9786131576164
Price: 789 CZK
Availability: InStock

Autor: Hédia Zardi

Jazyk:

Vazba: Brožovaná

Vydavatel: Omniscriptum

Dostupnost: Skladem u dodavatele

Odesíláme za 5-8 dnů

789 Kč

Most real world problems require the simultaneous optimization of multiple, competing, criteria (or...

Informace o knize

Autor

Hédia Zardi

Jazyk

Angličtina

Vazba

Kniha - Brožovaná

Vydáno

2018

Stránek

EAN

9786131576164

ISBN

6131576165

Enbook ID

07165112

Vydavatel

Omniscriptum

Hmotnost

122

Rozměry

152 x 229 x 5

Kompletní popis

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.

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