Design of experiments: robust design: seeking the best of all possible worlds
Proceedings of the 32nd conference on Winter simulation
Healthcare II: multi-objective simulation optimization for a cancer treatment center
Proceedings of the 33nd conference on Winter simulation
Multiobjective simulation optimization using an enhanced genetic algorithm
WSC '05 Proceedings of the 37th conference on Winter simulation
Simulation optimization for industrial scheduling using hybrid genetic representation
Proceedings of the 40th Conference on Winter Simulation
A simulation-based scheduling system for real-time optimization and decision making support
Robotics and Computer-Integrated Manufacturing
A web-based platform for the simulation-optimization of industrial problems
Computers and Industrial Engineering
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Many real-world production systems are complex in nature and it is a real challenge to find an efficient scheduling method that satisfies the production requirements as well as utilizes the resources efficiently. Tools like discrete event simulation (DES) are very useful for modeling these systems and can be used to test and compare different schedules before dispatching the best schedules to the targeted systems. DES alone, however, cannot be used to find the "optimal" schedule. Simulation-based optimization (SO) can be used to search for optimal schedules efficiently without too much user intervention. Observing that long computing time may prohibit the interest in using SO for industrial scheduling, various techniques to speed up the SO process have to be explored. This paper presents a case study that shows the use of a Web-based parallel and distributed SO platform to support the operations scheduling of a machining line in an automotive factory.