Abstract
Multi-facility location problem is a type of task often solved (not only) in logistics. It consists in finding the optimal location of the required number of centers for a given number of points. One of the possible solutions is to use the principle of the genetic algorithm. The Solver add-in, which uses the evolutionary method, is available in the Excel office software. It was used to solve the benchmark in 4 levels of difficulty (from 5 centers for 25 points to 20 centers for 100 points), and one task from practice. The obtained results were compared with the results obtained by the metaheuristic simulated annealing method. It was found that the results obtained by the evolutionary method are sufficiently accurate. Their accuracy depends on the complexity of the task and the performance of the HW used. The advantage of the proposed solution is easy availability and minimal requirements for user knowledge.
Highlights
IntroductionA typical example is finding the optimal location for c central warehouses that will serve b branches
The obtained results show that the use of the Excel-Solver software for solving multi-facility location problem (MFLP)
The accuracy of the results depends on the complexity of the task and the HW used
Summary
A typical example is finding the optimal location for c central warehouses that will serve b branches. In the literature, this problem is called the multi-facility location problem (MFLP) and there are a number of ways to solve this type of task. This problem is called the multi-facility location problem (MFLP) and there are a number of ways to solve this type of task This problem is often solved in the field of logistics, but there are other applications. The article is organized into five sections. In this introduction, our motivation and the objectives of this article are presented.
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