A multi-objective programming method for solving network DEA

The multi-objective programming model is proposed as an alternative approach for solving network DEA.The propositions concerning various cases of possible evaluation settings are developed.Case studies are implemented to examine the network DEA models with multi-objective programming. This study proposes the multi-objective programming (MOP) method for solving network DEA (NDEA) models. In the proposed method, the divisional efficiencies (within an organization) and the overall efficiency of the organization are formulated as separate objective functions in the multi-objective programming model. Compared with conventional DEA where the intermediate processes and products are ignored, this work measures the organization's overall efficiency without neglecting the efficiencies of its subunits. Two case studies demonstrate the proposed NDEA-MOP's utility in measuring the efficiencies of an organization with concerning interactive internal process.

[1]  Saad Mekhilef,et al.  A review on solar energy use in industries , 2011 .

[2]  Joe Zhu,et al.  Network DEA: Additive efficiency decomposition , 2010, Eur. J. Oper. Res..

[3]  Thomas R. Sexton,et al.  Network DEA: efficiency analysis of organizations with complex internal structure , 2004, Comput. Oper. Res..

[4]  Kaoru Tone,et al.  Network DEA: A slacks-based measure approach , 2009, Eur. J. Oper. Res..

[5]  Young-Jou Lai,et al.  Fuzzy Multiple Objective Decision Making , 2016 .

[6]  Feng-Jyh Lin,et al.  The Developing Strategy of Green Energy Industry Cluster A Case Study of the Solar Photoelectric Industry in Taiwan , 2012 .

[7]  N. Amjady,et al.  Stochastic Multiobjective Market Clearing of Joint Energy and Reserves Auctions Ensuring Power System Security , 2009, IEEE Transactions on Power Systems.

[8]  E. Lee,et al.  Fuzzy multiple objective programming and compromise programming with Pareto optimum , 1993 .

[9]  A. Charnes,et al.  Some Models for Estimating Technical and Scale Inefficiencies in Data Envelopment Analysis , 1984 .

[10]  Jamshid Aghaei,et al.  Multiobjective generation expansion planning considering power system adequacy , 2013 .

[11]  Nima Amjady,et al.  A scenario-based multiobjective operation of electricity markets enhancing transient stability , 2012 .

[12]  Hsing Hung Chen,et al.  Organizational forms for knowledge management in photovoltaic solar energy industry , 2010, Knowl. Based Syst..

[13]  Majid Nayeripour,et al.  Multi-objective placement and sizing of DGs in distribution networks ensuring transient stability using hybrid evolutionary algorithm , 2013 .

[14]  Mitsuo Gen,et al.  Network Models and Optimization: Multiobjective Genetic Algorithm Approach , 2008 .

[15]  Joe Zhu,et al.  Measuring performance of two-stage network structures by DEA: A review and future perspective , 2010 .

[16]  Taher Niknam,et al.  Improved particle swarm optimisation for multi-objective optimal power flow considering the cost, loss, emission and voltage stability index , 2012 .

[17]  Taher Niknam,et al.  Scenario-based multiobjective distribution feeder reconfiguration considering wind power using adaptive modified particle swarm optimisation , 2012 .

[18]  A. U.S.,et al.  Measuring the efficiency of decision making units , 2003 .

[19]  Kashem M. Muttaqi,et al.  Distribution expansion planning considering reliability and security of energy using modified PSO (Particle Swarm Optimization) algorithm , 2014 .

[20]  Taher Niknam,et al.  A modified honey bee mating optimization algorithm for multiobjective placement of renewable energy resources , 2011 .

[21]  Jamshid Aghaei,et al.  Generation Expansion Planning in pool market: A hybrid modified game theory and improved genetic algorithm , 2009 .

[22]  Taher Niknam,et al.  Multi-objective daily operation management of distribution network considering fuel cell power plants , 2011 .

[23]  Sabine Himmel Intertemporal Production Frontiers With Dynamic Dea , 2016 .

[24]  Abraham Charnes,et al.  Programming with linear fractional functionals , 1962 .

[25]  Nima Amjady,et al.  Multi-objective electricity market clearing considering dynamic security by lexicographic optimization and augmented epsilon constraint method , 2011, Appl. Soft Comput..

[26]  H. Zimmermann Fuzzy programming and linear programming with several objective functions , 1978 .

[27]  Hirofumi Fukuyama,et al.  Production , Manufacturing and Logistics Identifying the efficiency status in network DEA , 2012 .

[28]  Abraham Charnes,et al.  Measuring the efficiency of decision making units , 1978 .

[29]  Jamshid Aghaei,et al.  Dynamic security consideration in multiobjective electricity markets , 2014, Appl. Soft Comput..

[30]  Yih-Chearng Shiue,et al.  Applying analytic network process to evaluate the optimal recycling strategy in upstream of solar energy industry , 2012 .