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首页> 外文期刊>International Journal of Production Research >An exact penalty function method for optimising QAP formulation in facility layout problem
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An exact penalty function method for optimising QAP formulation in facility layout problem

机译:在设施布局问题中优化QAP公式的精确罚函数法

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A quadratic assignment problem (QAP), which is a combinatorial optimisation problem, is developed to model the problem of locating facilities with material flows between them. The aim of solving the QAP formulation for a facility layout problem (FLP) is to increase a system's operating efficiency by reducing material handling costs, which can be measured by interdepartmental distances and flows. The QAP-formulated FLP can be viewed as a discrete optimisation problem, where the quadratic objective function is optimised with respect to discrete decision variables subject to linear equality constraints. The conventional approach for solving this discrete optimisation problem is to use the linearisation of the quadratic objective function whereby additional discrete variables and constraints are introduced. The adoption of the linearisation process can result in a significantly increased number of variables and constraints; solving the resulting problem can therefore be challenging. In this paper, a new approach is introduced to solve this discrete optimisation problem. First, the discrete optimisation problem is transformed into an equivalent nonlinear optimisation problem involving only continuous decision variables by introducing quadratic inequality constraints. The number of variables, however, remains the same as the original problem. Then, an exact penalty function method is applied to convert this transformed continuous optimisation problem into an unconstrained continuous optimisation problem. An improved backtracking search algorithm is then developed to solve the unconstrained optimisation problem. Numerical computation results demonstrate the effectiveness of the proposed new approach.
机译:二次分配问题(QAP)是一种组合优化问题,用于对设施之间存在物料流的设施进行建模。解决设施布局问题(FLP)的QAP公式的目的是通过减少物料搬运成本来提高系统的运行效率,该成本可以通过部门间的距离和流量来衡量。可以将QAP公式化的FLP视为离散优化问题,其中针对受线性等式约束的离散决策变量优化二次目标函数。解决该离散优化问题的常规方法是使用二次目标函数的线性化,从而引入其他离散变量和约束。线性化过程的采用会导致变量和约束的数量大大增加;因此,解决所产生的问题可能具有挑战性。本文介绍了一种解决该离散优化问题的新方法。首先,通过引入二次不等式约束,将离散优化问题转化为仅包含连续决策变量的等效非线性优化问题。但是,变量的数量与原始问题相同。然后,使用精确的罚函数方法将这个变换后的连续优化问题转换成无约束的连续优化问题。然后,开发了一种改进的回溯搜索算法来解决无约束的优化问题。数值计算结果证明了该方法的有效性。

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