Cooperative coevolution of expressions for (r,Q) inventory management policies using genetic programming

• Type: Article in International Scientific Journal
• Date: 2019-03-05

Authors

Rui L.Lopes (Author) Other; Gonçalo Figueira (Author) FEUP; Pedro Amorim (Author) FEUP; Bernardo Almada Lobo (Author) FEUP

Journal

Title: International Journal of Production Research

Vol. 58 No. 2

Pages: 509-525

ISSN: 0020-7543

Publisher: Taylor & Francis

Indexing

ISI Web of Knowledge - 0 Citations

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Other information

Authenticus ID: P-00Q-MNM

DOI: 10.1080/00207543.2019.1597293

Abstract (EN): There are extensive studies in the literature about the reorder point/order quantity policies for inventory management, also known as (r,Q) policies. Over time different algorithms have been proposed to calculate the optimal parameters given the demand characteristics and a fixed cost structure, as well as several heuristics and meta-heuristics that calculate approximations with varying accuracy. This work proposes a new meta-heuristic that evolves closed-form expressions for both policy parameters simultaneously - Cooperative Coevolutionary Genetic Programming. The implementation used for the experimental work is verified with published results from the optimal algorithm, and a well-known hybrid heuristic. The evolved expressions are compared to those algorithms, and to the expressions of previous Genetic Programming approaches available in the literature. The results outperform the previous closed-form expressions and demonstrate competitiveness against numerical methods, reaching an optimality gap of less than (Formula presented.), while being two orders of magnitude faster. Moreover, the evolved expressions are compact, have good generalisation capabilities, and present an interesting structure resembling previous heuristics. © 2019, © 2019 Informa UK Limited, trading as Taylor & Francis Group.

Language: English

Type (Professor's evaluation): Scientific

No. of pages: 17