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.
Highlights
Information systems and their applications are often related to making some schedules, timetables of tasks or jobs with constrained resources
We consider job scheduling and optimization algorithms related to resources, time, and other constraints
It is usually difficult to perform a full binary recombination in real computer time, in order to schedule and optimize jobs, we may apply heuristic methods based on priority rules [4], evolution process ideas [5, 6], local search [7,8,9], variable neighborhood methods [10, 11], etc
Summary
Information systems and their applications are often related to making some schedules, timetables of tasks or jobs with constrained resources. The aim is to find such a schedule, which meets the requirements of job priority relations, resource constraints minimizing it by some criteria In many cases, this criterion is project’s finishing time. It is usually difficult to perform a full binary recombination in real computer time, in order to schedule and optimize jobs, we may apply heuristic methods based on priority rules [4], evolution process ideas [5, 6], local search [7,8,9], variable neighborhood methods [10, 11], etc. Computational results are given using data sets from project scheduling library (PSPLib) [14, 15]
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