A further study on inverse linear programming problems
Jianzhong Zhang,Zhenhong Liu +1 more
TLDR
In this article, Zhang et al. considered the problem of adjusting the cost coefficients of a given LP problem as less as possible so that a known feasible solution becomes the optimal one.About:
This article is published in Journal of Computational and Applied Mathematics.The article was published on 1999-06-30 and is currently open access. It has received 75 citations till now. The article focuses on the topics: Combinatorial optimization & Linear programming.read more
Citations
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Journal ArticleDOI
Inverse combinatorial optimization: A survey on problems, methods, and results
TL;DR: This work formalizes the notion of an inverse problem and its variants, and presents various methods for solving them.
Book
An Introduction to Polynomial and Semi-Algebraic Optimization
TL;DR: In this paper, a comprehensive introduction to the powerful moment approach for solving global optimization problems (and some related problems) described by polynomials (and even semi-algebraic functions) is presented.
Journal ArticleDOI
A novel inverse DEA model with application to allocate the CO2 emissions quota to different regions in Chinese manufacturing industries
TL;DR: A new inverse data envelopment analysis (InvDEA) model is developed and the empirical results based on the real data from Chinese manufacturing industries are obtained.
Journal ArticleDOI
Inverse Optimization for the Recovery of Market Structure from Market Outcomes: An Application to the MISO Electricity Market
TL;DR: In this paper, an inverse optimization-based methodology is proposed to determine market structure from commodity and transportation prices in locational marginal price-based electricity markets where prices are shadow prices in the centralized optimization used to clear the market.
Journal ArticleDOI
Inverse optimization for linearly constrained convex separable programming problems
Jianzhong Zhang,Chengxian Xu +1 more
TL;DR: This paper studies inverse optimization for linearly constrained convex separable programming problems that have wide applications in industrial and managerial areas and finds the parameter values that have the smallest adjustments.
References
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Book
"Data Envelopment Analysis: Theory, Methodology, and Applications"
TL;DR: In this article, the authors present DEA Software Packages for the U.S. Airline Industry and present a Spatial Efficiency Framework for the Support of Locational Decision (SELF).
Journal ArticleDOI
On an instance of the inverse shortest paths problem
D. Burton,Ph. L. Toint +1 more
TL;DR: An algorithm based on the Goldfarb-Idnani method for convex quadratic programming is proposed and analyzed for one of the instances of the inverse shortest paths problem in a graph.
Journal ArticleDOI
An inverse DEA model for inputs/outputs estimate
TL;DR: The problem is transformed into a multi-objective programming problem to solve, though in some special cases it can be answered by solving just one single-object LP problem.
Journal ArticleDOI
Calculating some inverse linear programming problems
Jianzhong Zhang,Zhenhong Liu +1 more
TL;DR: In this paper, a method for solving general inverse LP problems including upper and lower bound constraints is suggested, based on the optimality conditions for LP problems, and when applied to inverse minimum cost flow problem or inverse assignment problem, they are able to obtain strongly polynomial algorithms.
Journal ArticleDOI
On the use of an inverse shortest paths algorithm for recovering linearly correlated costs
D. Burton,Ph. L. Toint +1 more
TL;DR: This paper considers the inverse shortest paths problem where arc costs are subject to correlation constraints and a new method is proposed for solving this class of problems as a generalization of the algorithm presented in Burton and Toint (Mathematical Programming 53, 1992).