Computing and Selecting ε-Efficient Solutions of {0, 1}-Knapsack Problems

Emilia Tantar (), Oliver Schütze, José Rui Figueira, Carlos A. Coello Coello and El-Ghazali Talbi
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Emilia Tantar: Parc Scientifique de la Haute Borne 40

A chapter in Multiple Criteria Decision Making for Sustainable Energy and Transportation Systems, 2010, pp 379-389 from Springer

Abstract: Abstract This work deals with the computation and the selection of approximate – or ε-efficient – solutions of {0, 1}-knapsack problems. By allowing approximate solutions in general a much larger variety of possibilities for the underlying problem is offered to the decision maker. We enlighten the gap that can occur when passing ε-approximate solutions from the objective space into the parameter space (in terms of neighborhood). In this paper, we propose a novel adaptive ε-approximation based stochastic algorithm for the computation of the entire set of ε-efficient solutions, state a convergence result, and address the related decision making problem. For the latter we propose an interactive selection process which is intended to help the decision maker to understand the landscape of the obtained solutions.

Keywords: {0; 1}-Knapsack problems; Epsilon-adaptive method; Approximate solutions; Interactive selection procedure (search for similar items in EconPapers)
Date: 2010
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Persistent link: https://EconPapers.repec.org/RePEc:spr:lnechp:978-3-642-04045-0_32

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DOI: 10.1007/978-3-642-04045-0_32

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