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Design of experiments is often used to better understand or improve the output measures of a simulation model. Traditional cuboidal and spherical designs have been effective when the factor input regions are known. However, often in practice, simulation models have additional stochastic constraints causing the input factor space to be restricted and irregularly shaped. This paper looks into several...
The 0-1 knapsack problem (KP) is a classical NP-hard problem with binary decision variables. The traditional differential evolution (DE) is an effective stochastic parallel search evolutionary algorithm and customized to continuous function optimization. To solve KPs, based on DE, a discrete binary version of differential evolution (DBDE) was employed, where each component of a mutated vector component...
Artificial bee colony (ABC) algorithm is a new global stochastic optimization algorithm based on the particular intelligent behavior of honeybee swarms, in which there exists many issues to be improved and solved. When onlooker bees exploit in ABC algorithm, they choose food source depending on the strategy of proportional selection that can result in the premature of the evolutionary process. In...
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