Simulation-Based Scheduling of Waterway Projects Using a Parallel Genetic Algorithm

Ning Yang, Shiaaulir Wang and Paul Schonfeld
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Ning Yang: Parsons Corporation, New York, NY, USA
Shiaaulir Wang: Clarksville, MD, USA
Paul Schonfeld: Department of Civil and Environmental Engineering, University of Maryland, College Park, MD, USA

International Journal of Operations Research and Information Systems (IJORIS), 2015, vol. 6, issue 1, 49-63

Abstract: A Parallel Genetic Algorithm (PGA) is used for a simulation-based optimization of waterway project schedules. This PGA is designed to distribute a Genetic Algorithm application over multiple processors in order to speed up the solution search procedure for a very large combinational problem. The proposed PGA is based on a global parallel model, which is also called a master-slave model. A Message-Passing Interface (MPI) is used in developing the parallel computing program. A case study is presented, whose results show how the adaption of a simulation-based optimization algorithm to parallel computing can greatly reduce computation time. Additional techniques which are found to further improve the PGA performance include: (1) choosing an appropriate task distribution method, (2) distributing simulation replications instead of different solutions, (3) avoiding the simulation of duplicate solutions, (4) avoiding running multiple simulations simultaneously in shared-memory processors, and (5) avoiding using multiple processors which belong to different clusters (physical sub-networks).

Date: 2015
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