An effective estimation of distribution algorithm for the multi‐mode resource‐constrained project scheduling problem

In this paper, an estimation of distribution algorithm (EDA) is proposed to solve the multi‐mode resource‐constrained project scheduling problem (MRCPSP). In the EDA, the individuals are encoded based on the activity‐mode list (AML) and decoded by the multi‐mode serial schedule generation scheme (MSSGS), and a novel probability model and an updating mechanism are proposed for well sampling the promising searching region. To further improve the searching quality, a multi‐mode forward backward iteration (MFBI) and a multi‐mode permutation based local search method (MPBLS) are proposed and incorporated into the EDA based search framework to enhance the exploitation ability. Based on the design‐of‐experiment (DOE) test, suitable parameter combinations are determined and some guidelines are provided to set the parameters. Simulation results based on a set of benchmarks and comparisons with some existing algorithms demonstrate the effectiveness of the proposed EDA.