Anzeige
Erschienen in:
2009 | OriginalPaper | Buchkapitel
An Evolutionary Algorithm for the Multi-objective Multiple Knapsack Problem
verfasst von : Banu Soylu, Murat Köksalan
Erschienen in: Cutting-Edge Research Topics on Multiple Criteria Decision Making
Verlag: Springer Berlin Heidelberg
Aktivieren Sie unsere intelligente Suche, um passende Fachinhalte oder Patente zu finden.
Wählen Sie Textabschnitte aus um mit Künstlicher Intelligenz passenden Patente zu finden. powered by
Markieren Sie Textabschnitte, um KI-gestützt weitere passende Inhalte zu finden. powered by
In this study, we consider the multi-objective multiple knapsack problem (MMKP) and we adapt our favorable weight based evolutionary algorithm (FWEA) to approximate the efficient frontier of MMKP. The algorithm assigns fitness to solutions based on their relative strengths as well as their non-dominated frontiers. The relative strength is measured based on a weighted Tchebycheff distance from the ideal point where each solution chooses its own weights that minimize its distance from the ideal point. We carry out experiments on test data for MMKP given in the literature and compare the performance of the algorithm with several leading algorithms.