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The Product-Mix Problem under Stochastic Seasonal Demand

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  • S. D. Hodges
  • P. G. Moore

    (London Graduate School of Business Studies)

Abstract

The product-mix problem of production planning is to determine the best quantity of each product to manufacture, over a complete range of products competing for a number of limited resources. This paper examines the problem when uncertainty of demand is a major factor, making any differences between the penalties of over- and under-production important. In these circumstances the basic linear programming technique is insufficient, and a model has been developed as a multi-item newsboy problem in which a number of linear resource constraints affect the decision variables. The formulation is one of linear programming under uncertainty. A marginal analysis approach is used to obtain a detailed insight into the structure of the solution and to develop an effective computational procedure. Very little additional data is required, beyond that needed for a conventional linear program.

Suggested Citation

  • S. D. Hodges & P. G. Moore, 1970. "The Product-Mix Problem under Stochastic Seasonal Demand," Management Science, INFORMS, vol. 17(2), pages 107-114, October.
    • Handle: RePEc:inm:ormnsc:v:17:y:1970:i:2:p:b107-b114
    DOI: 10.1287/mnsc.17.2.B107
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    Cited by:

    1. Akif Bakir, M. & Byrne, Mike D., 1998. "Stochastic linear optimisation of an MPMP production planning model," International Journal of Production Economics, Elsevier, vol. 55(1), pages 87-96, June.
    2. Kumar Satyendra & Venkata Rao, V. & Tirupati Devanath, 2003. "Multiple products, multiple constraints, single period inventory problem: A Hierarchical solution procedure," IIMA Working Papers WP2003-11-03, Indian Institute of Management Ahmedabad, Research and Publication Department.
    3. Ng, T.S. & Lee, L.H. & Chew, E.P., 2006. "Build-pack planning for hard disk drive assembly with approved vendor matrices and stochastic demands," European Journal of Operational Research, Elsevier, vol. 175(2), pages 1117-1140, December.

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