Empirical comparison of search algorithms for discrete event simulation
Computers and Industrial Engineering
Healthcare II: multi-objective simulation optimization for a cancer treatment center
Proceedings of the 33nd conference on Winter simulation
Evolution strategies –A comprehensive introduction
Natural Computing: an international journal
Proceedings of the 35th conference on Winter simulation: driving innovation
Introduction to the special issue: Evolutionary algorithms for scheduling
Evolutionary Computation
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The Swedish Postal Services receives and distributes over 22 million pieces of mail every day. Mail transportation takes place overnight by airplanes, trains, trucks, and cars in a transportation network comprising a huge number of possible routes. For testing and analysis of different transport solutions, a discrete-event simulation model of the transportation network has been developed. This paper describes the optimization of transport solutions using evolutionary algorithms coupled with the simulation model. The vast transportation network in combination with a large number of possible transportation configurations and conflicting optimization criteria make the optimization problem very challenging. A large number of simulation evaluations are needed before an acceptable solution is found, making the computational cost of the problem severe. To address this problem, a computationally cheap surrogate model is used to offload the optimization process.