Use of Rules and Preferences for Schedule Builders in Genetic Algorithms for Production Scheduling
Selected Papers from AISB Workshop on Evolutionary Computing
Feature Article: Optimization for simulation: Theory vs. Practice
INFORMS Journal on Computing
Introduction to Evolutionary Computing
Introduction to Evolutionary Computing
Simulation-based optimization: practical introduction to simulation optimization
Proceedings of the 35th conference on Winter simulation: driving innovation
Distributed evolutionary algorithms for simulation optimization
IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans
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Pipeless plants are a new production concept in chemical engineering in which automated guided vehicles (AGVs) transport the substances in mobile vessels between processing stations. In the operation of such plants, decisions have to be made on the scheduling of the production, the assignment of the equipment and the routing of the AGVs that carry the vessels. The large number of interacting degrees of freedom prohibit the use of exact mathematical algorithms to compute optimal schedules. This paper describes the combination of an evolutionary scheduling algorithm with a simulation based schedule builder. The algorithm is tested on a real-life example and on a benchmark problem from the literature and yields considerably shorter makespans than a heuristic solution.