BPGA-EDA for the multi-mode resource constrained project scheduling problem

The Multi-mode Resource Constrained Project Scheduling Problem (MRCPSP) has been of research interest for over two decades. The problem is composed of two interacting sub problems: mode assignment and activity scheduling. These problems cannot be solved in isolation because of the interaction that exists between them. Many evolutionary algorithms have been applied to this problem most commonly the Genetic Algorithm (GA). It has been common practice to improve the performance of the GA with some local search techniques. The Bi-population Genetic Algorithm (BPGA) is one of the most competitive GAs for solving the MRCPSP. In this paper, we improve the BPGA by hybridising it with an Estimation of Distribution Algorithm that focuses on improving how modes are generated. We also suggest improvement to the existing experimental methodology.

[1]  Rubén Ruiz,et al.  Solving the Multi-Mode Resource-Constrained Project Scheduling Problem with genetic algorithms , 2003, J. Oper. Res. Soc..

[2]  Sönke Hartmann,et al.  A survey of variants and extensions of the resource-constrained project scheduling problem , 2010, Eur. J. Oper. Res..

[3]  Rainer Kolisch.  Serial and parallel resource-constrained project scheduling methods revisited: Theory and computation , 1994 .

[4]  Pedro Larrañaga,et al.  Estimation of Distribution Algorithms , 2002, Genetic Algorithms and Evolutionary Computation.

[5]  Mario Vanhoucke,et al.  A genetic algorithm for the preemptive and non-preemptive multi-mode resource-constrained project scheduling problem , 2010, Eur. J. Oper. Res..

[6]  Arno Sprecher,et al.  An exact algorithm for project scheduling with multiple modes , 1997 .

[7]  Mario Vanhoucke,et al.  An experimental investigation of metaheuristics for the multi-mode resource-constrained project scheduling problem on new dataset instances , 2014, Eur. J. Oper. Res..

[8]  Krzysztof Fleszar,et al.  An evolutionary algorithm for resource-constrained project scheduling , 2002, IEEE Trans. Evol. Comput..

[9]  R. Kolisch,et al.  Heuristic algorithms for the resource-constrained project scheduling problem: classification and computational analysis , 1999 .

[10]  James H. Patterson,et al.  ProGen/pix - An instance generator for resource-constrained project scheduling problems with partially renewable resources and further extensions , 2000, Eur. J. Oper. Res..

[11]  Woodie C. Flowers,et al.  A genetic algorithm for resource-constrained scheduling , 1996 .

[12]  Chen Fang,et al.  An effective estimation of distribution algorithm for the multi-mode resource-constrained project scheduling problem , 2012, Comput. Oper. Res..

[13]  Mario Vanhoucke,et al.  Using resource scarceness characteristics to solve the multi-mode resource-constrained project scheduling problem , 2011, J. Heuristics.

[14]  Omar S. Soliman,et al.  A Hybrid Estimation of Distribution Algorithm with Random Walk local Search for Multi-mode Resource-Constrained Project Scheduling problems , 2014, ArXiv.

[15]  F. F. Boctor.  Heuristics for scheduling projects with resource restrictions and several resource-duration modes , 1993 .

[16]  Pedro Larrañaga,et al.  GA-EDA: hybrid evolutionary algorithm using genetic and estimation of distribution algorithms , 2004 .

[17]  Federico Barber,et al.  An efficient hybrid genetic algorithm for scheduling projects with resource constraints and multiple execution modes , 2009 .

[18]  E Theodorsson-Norheim,et al.  Friedman and Quade tests: BASIC computer program to perform nonparametric two-way analysis of variance and multiple comparisons on ranks of several related samples. , 1987, Computers in biology and medicine.

[19]  Masao Mori,et al.  A genetic algorithm for multi-mode resource constrained project scheduling problem , 1997, Eur. J. Oper. Res..

[20]  S. Kumanan,et al.  Application of Petri Nets and a Genetic Algorithm to Multi-Mode Multi-Resource Constrained Project Scheduling , 2001 .

[21]  Rainer Kolisch,et al.  PSPLIB - A project scheduling problem library: OR Software - ORSEP Operations Research Software Exchange Program , 1997 .

[22]  Sönke Hartmann,et al.  Project Scheduling with Multiple Modes: A Genetic Algorithm , 2001, Ann. Oper. Res..

[23]  J. A. Lozano,et al.  Estimation of Distribution Algorithms: A New Tool for Evolutionary Computation , 2001 .

[24]  J. Ford,et al.  Hybrid estimation of distribution algorithm for global optimization , 2004 .