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Identifying efficient solutions via simulation: myopic multi-objective budget allocation for the bi-objective case

Branke, Juergen and Zhang, Wen (2019) 'Identifying efficient solutions via simulation: myopic multi-objective budget allocation for the bi-objective case.' OR Spectrum, 41 (3). 831 - 865. ISSN 0171-6468

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Abstract

Simulation optimisation offers great opportunities in the design and optimisation of complex systems. In the presence of multiple objectives, there is usually no single solution that performs best on all objectives. Instead, there are several Pareto-optimal (efficient) solutions with different trade-offs which cannot be improved in any objective without sacrificing performance in another objective. For the case where alternatives are evaluated on multiple stochastic criteria, and the performance of an alternative can only be estimated via simulation, we consider the problem of efficiently identifying the Pareto-optimal designs out of a (small) given set of alternatives. We present a simple myopic budget allocation algorithm for multi-objective problems and propose several variants for different settings. In particular, this myopic method only allocates one simulation sample to one alternative in each iteration. This paper shows how the algorithm works in bi-objective problems under different settings. Empirical tests show that our algorithm can significantly reduce the necessary simulation budget.

Item Type: Article
Divisions: Faculty of Social Sciences > Essex Business School
Faculty of Social Sciences > Essex Business School > Management Science and Entrepreneurship Group
Depositing User: Elements
Date Deposited: 15 Jul 2020 15:09
Last Modified: 18 Jul 2020 03:15
URI: http://repository.essex.ac.uk/id/eprint/28228

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