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Glowworm swarm optimisation algorithm for nonlinear fixed charge transportation problem in a single stage supply chain network

机译:单阶段供应链网络中非线性固定电荷运输问题的萤火虫群​​优化算法

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In this paper, Glowworm swarm optimisation (GSO) is proposed to solve nonlinear fixed charge transportation problem (NLFCTP) in a single stage supply chain network. In a fixed charge transportation problem, fixed cost is incurred for every route, along with the variable cost that is proportional to the amount shipped. In some cases, the variable cost is associated with quadratic variables in which the cost function will be nonlinear. This problem is more difficult to solve due to presence of the fixed costs that result in discontinuities in the objective function. The objective of this paper is to determine the least cost transportation plan that minimises the total variable and fixed costs while satisfying the supply and demand requirements of each plant and customer. The performance of GSO is compared in terms of total distribution cost with a spanning tree-based genetic algorithm. The comparison reveals that GSO provides better solutions.
机译:为了解决单阶段供应链网络中的非线性固定电荷运输问题,提出了萤火虫群优化算法(GSO)。在固定收费运输问题中,每条路线都会产生固定成本,并且可变成本与装运量成正比。在某些情况下,可变成本与二次函数相关联,在二次变量中,成本函数将是非线性的。由于存在导致目标函数不连续的固定成本,因此更难以解决此问题。本文的目的是确定最小成本的运输计划,以最小化总可变成本和固定成本,同时满足每个工厂和客户的供需需求。 GSO的性能在总分销成本方面与基于生成树的遗传算法进行了比较。比较表明,GSO提供了更好的解决方案。

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