Stephen E. Jacobsen
University of California, Los Angeles
10 Papers
110 Citations
Stephen E. Jacobsen is an academic researcher from University of California, Los Angeles. The author has contributed to research in topics: Convex analysis & Proper convex function. The author has an hindex of 7, co-authored 10 publications.
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Papers
Test problem construction for linear bilevel programming problems
TL;DR: A method of constructing test problems for linear bilevel programming problems is presented and selects a vertex of the feasible region, ‘far away’ from the solution of the relaxed linear programming problem, as the global solution of that problem.
26
Convergence of a Tuy-type algorithm for concave minimization subject to linear inequality constraints
TL;DR: A modification of Tuy's cone splitting algorithm for minimizing a concave function subject to linear inequality constraints is shown to be convergent by demonstrating that the limit of a sequence of constructed convex polytopes contains the feasible region as mentioned in this paper.
21
A level set algorithm for a class for reverse convex programs
TL;DR: In this paper, a new algorithm for minimizing a linear function subject to a set of linear inequalities and one additional reverse convex constraint is presented, which utilizes a conical partition of the convex polytope in conjuction with its facets.
18
Computational experience using an edge search algorithm for linear reverse convex programs
TL;DR: The purpose is to provide a collection of problems, with known optimal solutions, and performance information for an edge search implementation so that researchers may have some benchmarks with which to compare new methods for reverse convex programs or concave minimization problems.
17
A decision support system for regional hazardous waste management alternatives.
TL;DR: This paper, intended as a decision support tool for regional planning, incorporates information on the hazardous waste generation, treatment capacity and the costs of waste treatment alternatives into an optimization problem of finding the relationship between governing agency and the toxic waste producing firms.