Best-Order Crossover in an Evolutionary Approach to Multi-Mode Resource-Constrained Project Scheduling

Abstract

Multi-Mode Resource-Constrained Project Scheduling is an NP-hard optimization problem intensively studied due to its large area of applications. This paper concentrates on the evolutionary approaches to Multi-Mode Resource-Constrained Project Scheduling based on permutation encoded individuals. A new recombination operator is presented and a comparative analysis of several recombination operators is given based on computational experiments for several project instances. Numerical results emphasize a good performance of the proposed crossover scheme which takes into account information from the global best individual besides the genetic material from parents.