An Evolutionary Metahueristic for Approximating Preference-Nondominated Solutions

Murat Koksalan and Selcen Pamuk

Purdue University Economics Working Papers from Purdue University, Department of Economics

Abstract: We propose an evolutionary metaheuristic for approximating the preference-nondominated solutions of a decision maker in multiobjective combinatorial problems. The method starts out with some partial preference information provided by the decision maker, and utilizes an individualized fitness function to converge towards a representative set of solutions favored by the information at hand. The breadth of the set depends on the precision of the partial information available on the decision maker s preferences. The algorithm simultaneously evolves the population of solutions out towards the efficient frontier, focuses the population on those segments of the efficient frontier that will appeal to the decision maker, and disperses it over these segments to have an adequate representation. Simulation runs carried out on randomly generated instances of the Multiobjective Knapsack Problem and the Multiobjective Spanning Tree Problem have found the algorithm to yield highly satisfactory results.

Pages: 46 pages
Date: 2001
References: Add references at CitEc
Citations:

There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:pur:prukra:1146

Access Statistics for this paper

More papers in Purdue University Economics Working Papers from Purdue University, Department of Economics Contact information at EDIRC.
Bibliographic data for series maintained by Business PHD ().