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Multi-Objective Soft Computing-Based Approaches to Optimize Inventory-Queuing-Pricing Problem under Fuzzy Considerations

机译：基于多目标软计算的方法，以在模糊考虑下优化库存排队定价问题

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摘要

Due to uncertain environment, various parameters such as price, queuing length, warranty, and so on influence on inventory models. In this paper, an inventory-queuing-pricing problem with continuous review inventory control pol- icy and batch arrival queuing approach, is presented. To best of our knowledge, (1) demand function is stochastic and price dependent; (IL) due to the uncertainty in real-world situations, a fuzzy programming approach is applied. There- fore, the presented model with goal of maximizing total profit of system analyzes the price and order quantity decision variables. Since the proposed model belongs to NP-hard problems, Pareto-based approaches based on non-dominated ranking and sorting genetic algorithm are proposed and justified to solve the model. Several numerical illustrations are generated to demonstrate the model validity and algorithms performance. The results showed the applicability and robustness of the proposed soft-computing-based approaches to analyze the problem.
机译：由于环境不确定，各种参数，如价格，排队长度，保修等对库存模型的影响。本文介绍了连续审查库存控制策划和批量到达排队方法的清点排队定价问题。据我们所知，（1）需求功能是随机和价格依赖; （IL）由于现实世界情况的不确定性，应用了模糊的编程方法。因此，呈现的模型具有最大化系统总利润的目标，分析了价格和订单数量决策变量。由于所提出的模型属于NP难题，提出了基于非主导排名和分类遗传算法的基于帕累托的方法，并证明了解决模型。生成若干数值图形以演示模型有效性和算法性能。结果表明，所提出的基于软计算的方法的适用性和稳健性来分析问题。

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