Abstract
The double row layout problem is to arrange a number of machines on both sides of a straight aisle so as to minimize the total material handling cost. Aiming at the random distribution of product demands, we study a stochastic robust double row layout problem (SR-DRLP). A mixed integer programming (MIP) model is established for SR-DRLP. A surrogate model is used to linearize the nonlinear term in the MIP to achieve a mixed integer linear programming model, which can be readily solved by an exact method to yield high-quality solutions (layouts) for small-scale SR-DRLPs. Furthermore, we propose a hybrid approach combining a local search and an exact approach (LS-EA) to solve large-scale SR-DRLPs. Firstly, a local search is designed to optimize the machine sequences on two rows and the clearance from the most left machine on row 1 to the left boundary. Then, the exact location of each machine is further optimized by an exact approach. The LS-EA is applied to six problem instances ranging from 8 to 50 machines. Experimental results show that the surrogate model is effective and LS-EA outperforms the comparison approaches.
Highlights
Alessandro NiccolaiResearch on the facility layout problem (FLP) usually involves the arrangement of machines in a plant, which is of great significance for improving production efficiency and reducing cost [1]
For the dynamic processing environment in practice, in our previous work we studied a dynamic double row layout problem (DRLP), where a layout was designed for each processing period to minimize total material flow cost and rearrangement cost [6], and proposed a robust layout method for a robust DRLP [7]
Local is an effective heuristic combinatorial opthis paper, we propose a hybrid approach combining a local search and an exact approach timization problems and there are many studies [33,34,35] that apply this to solve FLPs
Summary
Research on the facility layout problem (FLP) usually involves the arrangement of machines in a plant, which is of great significance for improving production efficiency and reducing cost [1]. Studied a dynamic double row layout problem, where multiple processing periods are considered and material flows amongst machines are fixed during a specific period but change over different periods. They sought to design an effective layout for each processing period to minimize the sum of the material handling cost and the rearrangement cost of machines relocated in consecutive periods. We study a stochastic double row layout problem (SR-DRLP), which involves multiple processing periods, and product demands are independent normally distributed random variables. Utilizing the linearized MIP, the exact location of each machine is optimized by the exact approach
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