Capacity planning in manufacturing and computer networks

Article Abstract:

A branch and bound algorithm for planning capacity in manufacturing and computer networks is proposed. The algorithm globally minimizes a concave cost function over a single convex linear performance constraint and lower/upper bounds on discrete capacity variables. Reoptimization procedures are used to solve the subproblems more efficiently. Computational tests on problems with up to 100 variables indicate the efficacy of the algorithm for capacity planning.

Methods, Management, Industrial capacity, Capacity management (Computers), Capacity management (Information technology)

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Relative risk - value models

Article Abstract:

A relative risk-value model and a measure of risk for lotteries with positive results are proposed to provide more insights into decision making under risk. A decision can be achieved in a relative risk independence condition by distinctly trading off between the relative measure of risk and a measure of value, which can either be similar with some expected utility models or represent nonexpected utility preferences.

Utility theory, Utility functions

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The computation of the worst conditional expectation

Article Abstract:

A branch&bound method is developed to compute the worst conditional expectation (WCE) of a random variable Z. It is effective for many data sets and therefore can be applied in all the optimization problems where the decision maker must consider risk.

Random variables

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