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Designing and solving a bi-level model for rice supply chain using the evolutionary algorithms

机译:使用进化算法设计和解决大米供应链的双层模型

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According to the recent gigantic development in the agricultural section, Agricultural Supply Chain (ASC) management has attracted both researchers and agronomic practitioners. In this regard, rice as one of the important agricultural products is generally cultivated by rural farmers in small farmlands. Due to the high demand, high price, type of products, and also wide geographic range of production and consumption, the rice supply chain has special characteristics in ASC. In this regard, this paper not only firstly considers rice supply chain and but also proposes a bi-level optimization model for rice supply chain. The proposed model aims to minimize total cost with respect to the two decision makers' opinions. Since, the bi-level programming is NP-hard, to solve the proposed model, two well-known meta-heuristic algorithms including Genetic Algorithm (GA) and Particle Swarm Optimization (PSO) along with two hybrid algorithms (PSO-GA and GA-PSO) and a modified algorithm (GPA) are utilized. In order to fill the literature gaps and to get closer to real-world applications, an applicable example in Iran is studied. Based on the results and managerial insights, the GPA is chosen as the best method and its allocated value of the variable are reported. The results show that the proposed model and solution methods are valid, practical, and effective. Also, in order to provide an insight to the functionality of the model and the results of the case, some sensitivity analyses on the major model parameters such as the demand are provided.
机译:根据近期农业科的巨大发展,农业供应链(ASC)管理层吸引了研究人员和农艺从业人员。在这方面,赖斯作为重要农产品之一一般受到小农田农村农民的培养。由于需求量高,价格高,产品类型,以及各种地理范围的生产和消费,大米供应链具有特殊的ASC特性。在这方面,本文不仅首先考虑了大米供应链,而且还提出了一种用于米供应链的双层优化模型。拟议的型号旨在最大限度地减少两项决策者的意见的总成本。由于双级编程是NP - 硬,以解决所提出的模型,两个众所周知的元启发式算法,包括遗传算法(GA)和粒子群优化(PSO)以及两个混合算法(PSO-GA和GA -pso)和修改的算法(GPA)。为了填补文献差距并更接近现实世界的应用,研究了伊朗的适用示例。根据结果​​和管理见解,将GPA选择为最佳方法,并报告其变量的分配值。结果表明,拟议的模型和解决方案方法有效,实用,有效。此外,为了提供对模型的功能和案例的结果的洞察力,提供了一些对诸如需求的主要模型参数的敏感性分析。

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