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Solving fuzzy multiple objective generalized assignment problems directly via bees algorithm and fuzzy ranking

机译:通过蜜蜂算法和模糊排序直接解决模糊多目标广义分配问题

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In this paper, a direct solution approach for solving fuzzy multiple objective generalized assignment problems is proposed. In the problem, the coefficients and right hand side values of the constraints and the objective function coefficients are defined as fuzzy numbers. The addressed problem also has a multiple objective structure where the goals are determined so as to minimize the total cost and the imbalance between the workload of the agents. The direct solution approach utilizes the fuzzy ranking methods to rank the objective function values and to determine the feasibility of the constraints within a metaheuristic search algorithm, known as bees algorithm. Different fuzzy ranking methods, namely signed distance, integral value and area based approach are used in bees algorithm. For the computational study, the effects of these fuzzy ranking methods on the quality of the solutions are also analyzed.
机译:本文提出了一种直接解决模糊多目标广义分配问题的方法。在该问题中,约束的系数和右侧值以及目标函数系数被定义为模糊数。所解决的问题还具有多个目标结构,在该结构中确定了目标,以便最大程度地降低总成本和代理工作量之间的不平衡。直接解决方案方法利用模糊排序方法对目标函数值进行排序,并确定元启发式搜索算法(称为蜜蜂算法)中约束的可行性。蜜蜂算法使用了不同的模糊排序方法,即有符号距离,积分值和基于面积的方法。为了进行计算研究,还分析了这些模糊排序方法对解质量的影响。

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