Optimization of resource-constrained project schedules by simulated annealing and variable neighborhood search

Abstract

Abstract Applications of information technologies are often related to making some schedules, timetables of tasks or jobs with constrained resources. In this paper we consider job scheduling and optimization algorithms related to resources, time and other constraints. Schedule optimization procedures, based on schedule coding by priority list of jobs, are created and investigated. Optimal priority list of jobs is found by approaching algorithms of local and global search, namely, random search and simulated annealing methods with the variable neighborhood, defined by the decoding procedure applied. Computational results with testing data from project scheduling Library are given.