An adaptive large neighbourhood search for the operational integrated production and distribution problem of perishable products

• Type: Article in International Scientific Journal
• Date: 2015

Authors

Pedro Amorim (Author) FEUP; Bernardo Almada Lobo (Author) FEUP; Marcio Belo Filho (Author) FEUP

Journal

Title: International Journal of Production Research

Vol. 53

Pages: 6040-6058

ISSN: 0020-7543

Publisher: Taylor & Francis

Indexing

ISI Web of Knowledge - 41 Citations

ISI Web of Science

Scopus - 51 Citations

Scientific classification

FOS: Engineering and technology

CORDIS: Technological sciences

Associated Projects

BESTCASE-RL2 - Smart Manufacturing and Logistics

Other information

Authenticus ID: P-00G-F7D

DOI: 10.1080/00207543.2015.1010744

Resumo (PT): Production and distribution problems with perishable goods are common in many industries. For the sake of the competitiveness of the companies, the supply chain planning of products with restricted lifespan should be addressed with an integrated approach. Particularly at the operational level, the sizing and scheduling of production lots have to be decided together with vehicle routing decisions to satisfy the customers. However, such joint decisions make the problems hard to solve for industries with a large product portfolio. This paper proposes an adaptive large neighbourhood search (ALNS) framework to tackle the problem. This metaheuristic is well-known to be effective for vehicle routing problems. The proposed approach relies on mixed-integer linear programming models and tools. The adaptive large neighbourhood search outperforms traditional procedures of the literature, namely exact methods and x-and-optimize, in terms of quality of the solution and computational time of the algorithms. Nine in ten runs of ALNS yielded better solutions than traditional procedures and the best solution value found by the latter methods 12:7% greater than the former, on average.

Abstract (EN): Production and distribution problems with perishable goods are common in many industries. For the sake of the competitiveness of the companies, the supply chain planning of products with restricted lifespan should be addressed with an integrated approach. Particularly, at the operational level, the sizing and scheduling of production lots have to be decided together with vehicle routing decisions to satisfy the customers. However, such joint decisions make the problems hard to solve for industries with a large product portfolio. This paper proposes an adaptive large neighbourhood search (ALNS) framework to tackle the problem. This metaheuristic is well known to be effective for vehicle routing problems. The proposed approach relies on mixed-integer linear programming models and tools. The ALNS outperforms traditional procedures of the literature, namely, exact methods and fix-and-optimize, in terms of quality of the solution and computational time of the algorithms. Nine in ten runs of ALNS yielded better solutions than traditional procedures, outperforming on average 12.7% over the best solutions provided by the latter methods.

Language: English

Type (Professor's evaluation): Scientific

No. of pages: 19