A Noniterative Algorithm for the Multiproduct Production and Work Force Planning Problem

Discrete optimal control theory is used to develop an efficient noniterative algorithm for solving the multiproduct production and work force planning problems with a quadratic cost function. The quadratic cost models allow uncertainties to be handled directly because they minimize the expected cost...

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Vydáno v:Operations research Ročník 40; číslo 3; s. 620 - 625
Hlavní autor: Singhal, Kalyan
Médium: Journal Article
Jazyk:angličtina
Vydáno: Linthicum, MD INFORMS 01.05.1992
Operations Research Society of America
Institute for Operations Research and the Management Sciences
Témata:
Aggregate production
Algorithms
Applied sciences
Coefficients
Control theory
Cost efficiency
Cost functions
Efficiency
Exact sciences and technology
Inventory control, production control. Distribution
inventory/production
Mathematical models
Minimization of cost
nonlinear programming algorithms
Operational research and scientific management
Operational research. Management science
Operations research
Production efficiency
production smoothing, and linear decision rules
programming
Recurrence relations
Technical Notes
Theory
Workforce
Workforce planning
Manpower
Cost minimization
Experimental result
Production control
Quadratic cost
Planning
Multiple production
Algorithm
Optimization
ISSN:0030-364X, 1526-5463
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Shrnutí:Discrete optimal control theory is used to develop an efficient noniterative algorithm for solving the multiproduct production and work force planning problems with a quadratic cost function. The quadratic cost models allow uncertainties to be handled directly because they minimize the expected cost if unbiased expected demand forecasts are given. A real-world problem may involve as many as 200,000 variables. The noniterative algorithm makes the computations, irrespective of the number of products, not only feasible but also extremely easy and efficient.
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ISSN:0030-364X
1526-5463
DOI:10.1287/opre.40.3.620