期刊
INTERNATIONAL TRANSACTIONS IN OPERATIONAL RESEARCH
卷 30, 期 2, 页码 1144-1168出版社
WILEY
DOI: 10.1111/itor.12965
关键词
metaheuristics; Integer Programming; Logistics; Combinatorial Optimization; Automotive Industry
This work focuses on the internal logistics processes in SEAT S.A, a car assembling company. It proposes an integer linear programming model and a simulation-based iterated local search algorithm to solve the in-house logistics routing problem. The experimental results demonstrate the effectiveness of the proposed methods in improving the company's processes.
In this work, we consider the internal logistics processes in the car assembling company SEAT S.A (where SEAT is Sociedad Espanola de Automoviles de Turismo). We focus on the design of the supplying routes from the warehouse toward the workstations along a production line. The in-house logistics routing problem (ILRP) can be seen as an extension of the classical vehicle routing problem considering special features such as long-term fixed routes, unknown orders, backorders, and homogeneous fleet. To solve the ILRP, we propose an integer linear programming (ILP) model and a simulation-based iterated local search (SimILS) algorithm. We conduct two computational experiments. The first experiment analyzes the methods' performance, and the second experiment compares the SimILS results with the current company's routes, considering real data provided by SEAT S.A. The results show that the SimILS provides the best overall results overcoming both the ILP approach and the current company's solution, leading to a significant improvement in the company's processes.
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