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Constraints reduction programming by subset selection: a study from numerical aspect

Yuan Shen(ocsiban***at***126.com)

Abstract: We consider a novel method entitled constraints reduction programming which aims to reduce the constraints in an optimization model. This method is derived from various applications of management or decision making, and has potential ability to handle a wider range of applications. Due to the high combinatorial complexity of underlying model, it is difficult to obtain a global solution. Instead, we propose three efficient greedy approaches for solving it. Preliminary experimental results show that the proposed approaches can obtain satisfactory results.

Keywords: optimization, constraints reduction, combinatoric complexity, mixed integer programming, big M method, backward selection, greedy method

Category 1: Applications -- OR and Management Sciences

Category 2: Integer Programming (0-1 Programming )

Category 3: Convex and Nonsmooth Optimization (Convex Optimization )

Citation: Tech Report 1703, Nanjing University of Finance & Economics, 2017

Download: [PDF]

Entry Submitted: 09/24/2017
Entry Accepted: 09/25/2017
Entry Last Modified: 09/24/2017

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