PSO with path relinking for resource allocation using simulation optimization

This paper proposes a PSO-based optimization approach with a particular path relinking technique for moving particles. PSO is evaluated for two combinato rial problems. One under uncertainty, which represents a new application of PSO with path relinking in a stochastic scenario. PSO is considered first in a deterministic scenario for solving the Task Assignme nt Problem (TAP) and hereafter for a resource allocation problem in a petroleum terminal. This is considered for evaluating PSO in a problem subject to uncertain ty whose performance can only be evaluated by simulation. In this case, a discrete event simulation is built for modeling a real-world facility whose typical operations of receiving and transferring oil from tankers to a refinery are made through intermediary storage tanks. The simulation incor porates uncertain data and operational details for optimization that are not considered in other mathematical optimi zation models. Experiments have been carried out considering issues that affect the choice of parameters for both optimization and simulation. The results show advantages of the proposed approach when compared with Genetic Algorithm and OptQuest (a commercial opt imization package). 2013 Elsevier Ltd. All rights reserved.