A hybrid VNS approach for the short-term production planning and scheduling: A case study in the pulp and paper industry

• Type: Article in International Scientific Journal
• Date: 2013

Authors

Gonçalo Figueira (Author) FEUP; Maristela Oliveira Santos (Author) Other; Bernardo Almada Lobo (Author) FEUP

Journal

Title: Computers and Operations Research

Vol. 40 No. 7

Pages: 1804-1818

ISSN: 0305-0548

Publisher: Elsevier

Indexing

ISI Web of Knowledge - 17 Citations

Scopus - 25 Citations

INSPEC

COMPENDEX

Scientific classification

FOS: Natural sciences > Computer and information sciences

Other information

Authenticus ID: P-004-ZYA

DOI: 10.1016/j.cor.2013.01.015

Abstract (EN): Mathematical formulations for production planning are increasing complexity, in order to improve their realism. In short-term planning, the desirable level of detail is particularly high. Exact solvers fail to generate good quality solutions for those complex models on medium- and large-sized instances within feasible time. Motivated by a real-world case study in the pulp and paper industry, this paper provides an efficient solution method to tackle the short-term production planning and scheduling in an integrated mill. Decisions on the paper machine setup pattern and on the production rate of the pulp digester (which is constrained to a maximum variation) complicate the problem. The approach is built on top of a mixed integer programming (MIP) formulation derived from the multi-stage general lotsizing and scheduling problem. It combines a Variable Neighbourhood Search procedure which manages the setup-related variables, a specific heuristic to determine the digester's production speeds and an exact method to optimize the production and flow movement decisions. Different strategies are explored to speed-up the solution procedure and alternative variants of the algorithm are tested on instances based on real data from the case study. The algorithm is benchmarked against exact procedures. (C) 2013 Elsevier Ltd. All rights reserved.

Language: English

Type (Professor's evaluation): Scientific

No. of pages: 15