Home // International Journal On Advances in Software, volume 13, numbers 3 and 4, 2020 // View article

The Matching Lego(R)-Like Bricks Problem: A Metaheuristic Approach

Authors:
Martin Zinner
Rui Song
Kim Feldhoff
André Gellrich
Wolfgang E. Nagel

Keywords: Constraint satisfaction problem; Combinatorial problem; Genetic algorithm; Crossover; Mutation; Multi-objective optimization; Apache Commons Math.; jMetal.

Abstract:
We formulate and transform a real-world combinatorial problem into a constraint satisfaction problem: choose a restricted set of containers from a warehouse, such that the elements contained in the containers satisfy some restrictions and compatibility criteria. We set up a formal, mathematical model, describe the combinatorial problem and define a (nonlinear) system of equations, which describes the equivalent constraint satisfaction problem. Next, we use the framework provided by the Apache Commons Mathematics Library in order to implement a solution based on genetic algorithms. We carry out performance tests and show that a general approach, having business logic solely in the definition of the fitness function, can deliver satisfactory results for a real-world use case in the manufacturing industry. To conclude, we use the possibilities offered by the jMetal framework to extend the use case to multi-objective optimization and and compare different heuristic algorithms predefined in jMetal applied to our use case.

Pages: 160 to 181

Copyright: Copyright (c) to authors, 2020. Used with permission.

Publication date: December 30, 2020

Published in: journal

ISSN: 1942-2628