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Solving Optimal Pricing Model for Perishable Commodities with Imperialist Competitive Algorithm

机译:用帝国主义竞争算法求解易逝品最优定价模型。

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The pricing problem for perishable commodities is important in manufacturing enterprise. In this study, a new model based on the profit maximization principle and a discrete demand function which is a negative binomial demand distribution is proposed. This model is used to find out the best combination for price and discount price. The computational results show that the optimal discount price equals the cost of the product. Because the demand functions which involves several different distributions is so complex that the model is hard to solve with normal numerical method. Thus we combine the model with exterior penalty function and applied a novel evolution algorithm-Imperialist Competitive Algorithm (ICA) to solve the problem. Particle Swarm algorithm (PSO) is also applied to solve the problem for comparison. The result shows that ICA has higher convergence rate and execution speed.
机译:易腐商品的定价问题在制造企业中很重要。本研究提出了一种基于利润最大化原理和离散需求函数的负二项式需求分布新模型。该模型用于找出价格和折扣价的最佳组合。计算结果表明,最优折扣价等于产品成本。由于涉及多个不同分布的需求函数非常复杂,因此很难用正态数值方法求解该模型。因此,我们将模型与外部惩罚函数相结合,并应用了一种新的进化算法-帝国主义竞争算法(ICA)来解决该问题。粒子群算法(PSO)也被用来解决比较问题。结果表明,ICA具有较高的收敛速度和执行速度。

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