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An Outer Approximation Method for Globally Minimizing a Concave Function over a Compact Convex Set

T. V. Thieu
- Vol. 8
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The article was published on 1983-01-01 and is currently open access. It has received 58 citations till now. The article focuses on the topics: Concave function & Convex set.

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Journal ArticleDOI

A two‐phase decomposition method for optimal design of looped water distribution networks

TL;DR: In this article, a two-phase decomposition method is proposed for the optimal design of new looped water distribution networks as well as for the parallel expansion of existing ones, where the main feature of the method is that it generates a sequence of improving local optimal solutions.
Journal ArticleDOI

An Outer Approximation Algorithm for Generating AllEfficient Extreme Points in the Outcome Set of a Multiple ObjectiveLinear Programming Problem

TL;DR: The results tangibly demonstrate the usefulness of using the outcome set approach of the Outer Approximation Algorithm instead of a decision set-based approach.
Journal ArticleDOI

Convex programs with an additional reverse convex constraint

TL;DR: In this paper, a method for solving a class of global optimization problems of the form (P): minimizef(x), subject tox∈D,g(x)≥0, whereD is a closed convex subset of Rn and f,g are convex finite functionsRn.
Book ChapterDOI

Concave Minimization: Theory, Applications and Algorithms

TL;DR: The purpose of this chapter is to present the essential elements of the theory, applications, and solution algorithms of concave minimization, including three fundamental classes of solution approaches that use deterministic (rather than stochastic) methods.

Assortment Planning under the Multinomial Logit Model with Totally Unimodular Constraint Structures

TL;DR: This paper considers constrained assortment optimization problems assuming that customers select according to the multinomial logit model (MNL) or according to other more general attraction choice models and shows that this fractional binary problem can be solved as an equivalent linear program.