Multi-criteria scheduling optimization with genetic algorithms
Igor Bernik, Mojca Bernik
Abstract
Igor Bernik, Mojca Bernik
Abstract
Multi-criteria scheduling optimization with genetic algorithms is described. Scheduling optimization methodology provides the planner with a quick and efficient scheduling method and enables him/her to experiment and decide which of the suitable solutions will become the production plan. The scheduling system is composed of a business information system - a database, a discrete event simulation model and a scheduling algorithm. The purpose of the integrated system is to help operative management personnel with production scheduling and planning. By comparing various scheduling methods, we established that the system utilizing genetic algorithms and simulation yielded from 5% to 15% better scheduling within a shorter time compared to manual scheduling.
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Multi-criteria scheduling optimization with genetic algorithms is described. Scheduling optimization methodology provides the planner with a quick and efficient scheduling method and enables him/her to experiment and decide which of the suitable solutions will become the production plan. The scheduling system is composed of a business information system - a database, a discrete event simulation model and a scheduling algorithm. The purpose of the integrated system is to help operative management personnel with production scheduling and planning. By comparing various scheduling methods, we established that the system utilizing genetic algorithms and simulation yielded from 5% to 15% better scheduling within a shorter time compared to manual scheduling.
Key concepts: Fair-share scheduling, Two-level scheduling, Rate-monotonic scheduling, Dynamic priority scheduling, Computer science, Genetic algorithm scheduling, Flow shop scheduling, Lottery scheduling