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A review of mathematical programming models for strategic capacity planning in manufacturing

Carme Martínez-Costa, Marta Mas-Machuca, Ernest Benedito and Albert Corominas

International Journal of Production Economics, 2014, vol. 153, issue C, 66-85

Abstract: This paper offers an up-to-date review on strategic capacity planning in manufacturing companies, with two main objectives: (1) to describe and analyze the strategic capacity planning problems; and (2) to review the mathematical programming models proposed in the literature for dealing with these problems. The main search was conducted in the Web of Science using critical keywords and was complemented by using other search engines. Cross checking of citations of all the articles was also carried out. Papers were selected that have formulated discrete time, finite horizon, multi-period models. The major decisions addressed and the main conditioning factors of the strategic capacity problem in the literature are identified and described. A structured overview of the main strategic capacity planning mathematical programming models is given. A classification of the models is proposed and their main characteristics, solution procedures and industrial applications are identified. Based on the review of the existing studies, a framework for capacity planning is presented, consisting of three main phases: problem definition (considering context, characteristics of the manufacturing system and specific factors that could influence the decision-making process), model design and solution procedure. Closing the paper, some future lines of research are suggested. The review should help both practitioners and academic researchers in developing useful models and processes to aid decision-making in strategic capacity planning.

Keywords: Strategic capacity planning; Dynamic capacity planning; Mathematical programming models (search for similar items in EconPapers)
Date: 2014
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Citations: View citations in EconPapers (27)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:proeco:v:153:y:2014:i:c:p:66-85

DOI: 10.1016/j.ijpe.2014.03.011

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