OPTIMIZATION OF RESOURCE CONSTRAINED PROJECT SCHEDULES BY GENETIC ALGORITHM BASED ON THE JOB PRIORITY LIST

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 algorithms of job scheduling related to resources, time, and other constraints. Schedule optimization procedures, based on schedule coding by the priority list of jobs, are created and investigated. The optimal priority list of jobs is found by applying the algorithms of local and global search, namely, Genetic Algorithm with constructed crossover, mutation, and selection operators, based on the job priority list. Computational results with testing data from the project scheduling problem library are given.