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In this paper, we propose a direct search algorithm based on kernel density estimator for the nonlinear optimization problems. It estimates the objective function by the kernel density estimator with the local samples only, and then approximates the ascent direction of the objective function with the one of the estimator. The proposed optimization approach features the derivative-free with much likely...
To approximate the Pareto optimal solutions of a multi-objective optimization problem, Zhang and Li have recently developed a novel multi-objective evolutionary algorithm based on decomposition(MOEA/D). It can work well if the curve shape of the Pareto-optimal front is friendly. Otherwise, it might fail. In this paper, we propose an improved MOEA/D algorithm (denoted as TMOEA/D), which utilizes a...
The existing shelf space allocation methods only optimize the profits without considering the sales time. Actually, the time to sale the products is important as well to retailers because the time has a significant impact on the liquidity and long-term profits of a retail shop. Hence, this paper proposes a bi-objective model, in which one objective is to maximize the total profits of all store's products...
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