Title: Municipal waste management optimisation using a firefly algorithm-driven simulation-optimisation approach
Authors: Julian Scott Yeomans; Xin-She Yang
Addresses: OMIS Area, Schulich School of Business, York University, 4700 Keele Street, Toronto, ON, M3J 1P3, Canada ' Department of Design Engineering and Mathematics, School of Science and Technology, Middlesex University, Hendon Campus, London NW4 4BT, UK
Abstract: Many municipal solid waste management decision-making applications contain considerable elements of stochastic uncertainty. Simulation-optimisation techniques can be adapted to model a wide variety of problem types in which system components are stochastic. The family of optimisation methods referred to as simulation-optimisation incorporate stochastic uncertainties expressed as probability distributions directly into their computational procedures. In this paper, a new simulation-optimisation approach is presented that implements a modified version of the computationally efficient, nature-inspired firefly algorithm (FA). The effectiveness of this stochastic FA-driven simulation-optimisation procedure for optimisation is demonstrated using a municipal solid waste management case study.
Keywords: simulation; optimisation; bio-inspired metaheuristics; firefly algorithm; solid waste management; municipal solid waste; MSW; stochastic uncertainty; case study.
International Journal of Process Management and Benchmarking, 2014 Vol.4 No.4, pp.363 - 375
Published online: 28 Oct 2014 *Full-text access for editors Access for subscribers Purchase this article Comment on this article