Solving the bi-objective integer programming: A DEA methodology

E Keshavarz, M Toloo - 2014 international conference on …, 2014 - ieeexplore.ieee.org
2014 international conference on control, decision and information …, 2014ieeexplore.ieee.org
Finding and classifying all efficient solutions for a Bi-Objective Integer Linear Programming
(BOILP) problem is one of the controversial issues in Multi-Criteria Decision Making
problems. The main aim of this study is to utilize the well-known Data Envelopment Analysis
(DEA) methodology to tackle this issue. Toward this end, we first state some propositions to
clarify the relationships between the efficient solutions of a BOILP and efficient Decision
Making Units (DMUs) in DEA and next design a new two-stage approach to find and classify …
Finding and classifying all efficient solutions for a Bi-Objective Integer Linear Programming (BOILP) problem is one of the controversial issues in Multi-Criteria Decision Making problems. The main aim of this study is to utilize the well-known Data Envelopment Analysis (DEA) methodology to tackle this issue. Toward this end, we first state some propositions to clarify the relationships between the efficient solutions of a BOILP and efficient Decision Making Units (DMUs) in DEA and next design a new two-stage approach to find and classify a set of efficient solutions. Stage I formulates a two-phase Mixed Integer Linear Programming (MILP) model, based on the Free Disposal Hull (FDH) model in DEA, to gain a Minimal Complete Set of efficient solutions. Stage II uses a variable returns to scale DEA model to classify the obtained efficient solutions from Stage I as supported and non-supported. A BOILP model containing 6 integer variables and 4 constraints is solved as an example to illustrate the applicability of the proposed approach.
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