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Penalty Rules in Multicriteria Genetic Search

In: New State of MCDM in the 21st Century

Author

Listed:
  • Grzegorz Koloch

    (Warsaw School of Economics)

  • Tomasz Szapiro

    (Warsaw School of Economics)

Abstract

In the paper, by means of numerical experiments conducted on artificially constructed problem instances, we test penalty rules for constrained genetic optimization of the Capacitated Heterogeneous Vehicle Routing Problem with Time-Windows in a bi-objective framework. Optimized criteria are cost minimization and capacity utilization maximization. Two approaches are employed – scalarization of objectives and dominance-based evaluation of solutions. We show that it is possible to handle infeasibility in such a way, that this risk of divergence to regions of infeasibility is acceptable. The most secure penalty rule among the tested ones turns out to be the rule which explicitly controls the proportion of infeasible solutions in the population. This rule, along with the rule which accounts only the notion of solutions distance from the feasible set, outperforms rules based on time-penalties and best to best-feasible solution comparison over considered case studies.

Suggested Citation

  • Grzegorz Koloch & Tomasz Szapiro, 2011. "Penalty Rules in Multicriteria Genetic Search," Lecture Notes in Economics and Mathematical Systems, in: Yong Shi & Shouyang Wang & Gang Kou & Jyrki Wallenius (ed.), New State of MCDM in the 21st Century, chapter 0, pages 91-102, Springer.
    • Handle: RePEc:spr:lnechp:978-3-642-19695-9_8
    DOI: 10.1007/978-3-642-19695-9_8
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