The change of Intellectual Property Protection ( IPP) from a softer process patenting to a stronger product patenting in Indian Pharmaceutical Industry ( IPI) is attracting many global drug majors to source their prod...
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The change of Intellectual Property Protection ( IPP) from a softer process patenting to a stronger product patenting in Indian Pharmaceutical Industry ( IPI) is attracting many global drug majors to source their production from India, which is the fourth largest producer of pharmaceuticals in the world. In this paper, the interests of different stake holders like the buyers ( multinational enterprises), who are searching for efficient partners and the vendors ( Indian drug producers) that are competing for the contracts, are analysed for a suitable efficiency evaluation criterion. The primary objective of this paper is to study how various firms in the IPI with different business strategies, competing for the same opportunities can find suitable benchmarking peer groups to meet the challenges of a dynamic business environment using data envelopment analysis ( DEA). A multipleobjective DEA model that determines suitable peer groups for inefficient companies is discussed along with more traditional DEA models. The proposed model has the flexibility to include inputs like R& D expenditure and outputs like Exports that are not homogeneously distributed across the firms and address the interests of various stake holders like buyers and vendors simultaneously.
作者：
Ebrahimnejad, AliTavana, MadjidIslamic Azad Univ
Dept Math Qaemshahr Branch Qaemshahr Iran La Salle Univ
Lindback Distinguished Chair Informat Syst & Deci Business Syst & Analyt Dept Philadelphia PA 19141 USA Univ Paderborn
Fac Business Adm & Econ Business Informat Syst Dept D-33098 Paderborn Germany
Data Envelopment Analysis (DEA) is a mathematical programming technique for identifying efficient Decision Making Units (DMUs) with multiple inputs and multiple outputs. DEA provides a technical efficiency score for e...
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Data Envelopment Analysis (DEA) is a mathematical programming technique for identifying efficient Decision Making Units (DMUs) with multiple inputs and multiple outputs. DEA provides a technical efficiency score for each DMU, a technical efficiency reference set with peer DMUs, and a target for the inefficient DMU. The target unit informs the Decision Maker (DM) of the amount (%) by which an inefficient DMU should decrease its inputs and/ or increase its outputs to become efficient. However, the conventional DEA models generally do not consider the DM's preference structure in identifying the target units. Several equivalence models between the output-oriented DEA and multiple objective linear programming (MOLP) models have been proposed in the literature to take the DMs' preferences into consideration. However, these models are not able to identify target units when undesirable outputs are produced with desirable outputs in the production process. In this study we obtain a new link between a BCC model and the weighted minimax reference point of the MOLP formulation that simultaneously and interactively considers the increase in the total desirable outputs and the decrease in the total undesirable outputs. We present a pilot study for the North Atlantic Treaty Organization (NATO) enlargement problem to demonstrate the applicability of the proposed method and exhibit the efficacy of the procedures and algorithms. (C) 2014 Elsevier Ltd. All rights reserved.
Various computational difficulties arise in using decision set-based vector maximization methods to solve multiple objective linear programming problems. As a result, several researchers have begun to explore the poss...
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Various computational difficulties arise in using decision set-based vector maximization methods to solve multiple objective linear programming problems. As a result, several researchers have begun to explore the possibility of solving these problems by examining subsets of their outcome sets, rather than of their decision sets. In this article, we present and validate a basic weight set decomposition approach for generating the set of all efficient extreme points in the outcome set of a multipleobjectivelinear program. Based upon this approach, we then develop an algorithm, called the Weight Set Decomposition Algorithm, for generating this set. A sample problem is solved using this algorithm,and the main potential computational and practical advantages of the algorithm are indicated. (C) 2002 Elsevier Science B,V. All rights reserved.
In recent years, the concept of industrial symbiosis (IS) has led to improvements in resource efficiency that may not be possible with individual industrial plants acting independently. One specific aspect is to achie...
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In recent years, the concept of industrial symbiosis (IS) has led to improvements in resource efficiency that may not be possible with individual industrial plants acting independently. One specific aspect is to achieve economies of scale by having multiple companies located in close proximity in order to share common utilities, such as chilled and cooling water. Together, these industrial plants may form an inter-plant chilled and cooling water network (IPCCWN) to achieve greater overall cost savings. Some issues faced by an IPCCWN include network reliability problems due to the consistency of sources' availability, and cost savings allocations for IPCCWN synthesis due to the subjectivity of human preference on decision making. Thus, there exists a need for a decision-making tool to determine a feasible solution that will satisfy all industrial plants in the IPCCWN. In this work, a multi-objectivelinearprogramming model is developed to synthesize IPCCWN that achieves maximum cost savings. Next, a Pareto optimal solution is selected using fuzzy analytic hierarchy process (FAHP) approach. This solution gives the best balance of performance for a set of pre-defined qualitative and quantitative criteria, which is able to account for subjectivity that cannot be addressed from a purely mathematical programming standpoint. @ 2015 Elsevier Ltd. All rights reserved.
In this paper the possibility of the identification of a complete fuzzy decision (not only the maximizing alternative) in fuzzy linearprogramming by use of the parametric programming technique is presented. Also, it ...
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In this paper the possibility of the identification of a complete fuzzy decision (not only the maximizing alternative) in fuzzy linearprogramming by use of the parametric programming technique is presented. Also, it is shown that this fact can be useful in the Zimmermann approach to multiple objective linear programming. The presented remarks are illustrated by some numerical examples.
A multipleobjective model for manpower planning in a company sized, 100 person,military reserve unit was developed and tested. The model involves five objectives and consists of over 1150 decision variables and 650 c...
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A multipleobjective model for manpower planning in a company sized, 100 person,military reserve unit was developed and tested. The model involves five objectives and consists of over 1150 decision variables and 650 constraints over a 12 month planning horizon. US Army Reserve officers were used as subjects in an experiment in which model solutions were generated interactively using two different solution procedures. One procedure asked subjects-to identify their most preferred solution from a set of candidate solutions at each stage of the interactive process, while the other procedure asked subjects to identify their least preferred solution.
Halme et al. [M. Halme, T. Joro, P. Korhonen, S. Salo, J. Wallenius, A value efficiency approach to incorporating preference information in data envelopment analysis, Management Science 45 (1) (1999) 103-115] proposed...
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Halme et al. [M. Halme, T. Joro, P. Korhonen, S. Salo, J. Wallenius, A value efficiency approach to incorporating preference information in data envelopment analysis, Management Science 45 (1) (1999) 103-115] proposed value efficiency analysis as an approach to incorporate preference information in Data Envelopment Analysis (DEA). In this paper, we develop some related concepts, and present a refinement to Halme et al.'s approach to measure value efficiency scores more precisely. For do this, we will introduce an MOLP model which its objective functions are input/output variables subject to the defining constraints of Production Possibility Set (PPS) of DEA models. Then by using the so-called Zionts-Wallenius method, we aid the Decision Maker (DM) in searching for the Most Preferred Solution (MPS) and generating input/output weights as the DM's underlying value structure about objective functions. Finally, value efficiency scores are calculated by comparing the inefficient units to units having the same value as the MPS. (C) 2011 Elsevier Inc. All rights reserved.
The value efficiency approach is one possible way of incorporating information preferences into performance analysis of Decision-Making Units (DMUs). In this paper, we propose a novel geometric interpretation of value...
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The value efficiency approach is one possible way of incorporating information preferences into performance analysis of Decision-Making Units (DMUs). In this paper, we propose a novel geometric interpretation of value efficiency while plugging it into radial and non-radial DEA (Data Envelopment Analysis) models under the assumption of variable returns to scale. In addition, this novel geometric interpretation of value efficiency is extended to Additive Slacks-Based Measure (ASBM) modeling. This is achieved by linearization of non-radial DEA models using multi-objectiveprogramming. Performance of such proposed approaches in terms of reliability and discriminatory power are compared through a case study involving Finish bank branches. Research implications are then derived and conclusions are drawn. (c) 2021 Elsevier B.V. All rights reserved.
This paper suggests a method for finding efficient hyperplanes with variable returns to scale the technology in data envelopment analysis (DEA) by using the multiple objective linear programming (MOLP) structure. By p...
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This paper suggests a method for finding efficient hyperplanes with variable returns to scale the technology in data envelopment analysis (DEA) by using the multiple objective linear programming (MOLP) structure. By presenting an MOLP problem for finding the gradient of efficient hyperplanes, We characterize the efficient faces. Thus, without finding the extreme efficient points of the MOLP problem and only by identifying the efficient faces of the MOLP problem, we characterize the efficient hyperplanes which make up the DEA efficient frontier. Finally, we provide an algorithm for finding the efficient supporting hyperplanes and efficient defining hyperplanes, which uses only one linearprogramming problem. Published by Elsevier B.V.
A DEA-oriented Interactive Minimax Reference Point (DEA-IMRP) approach was recently developed to support integrated performance assessment and target setting for consistent management control and planning. To conduct ...
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A DEA-oriented Interactive Minimax Reference Point (DEA-IMRP) approach was recently developed to support integrated performance assessment and target setting for consistent management control and planning. To conduct the Integrated Efficiency and Trade-off (JET) analyses using the DEA-IMRP approach, it is important to understand the characteristics of the efficiency frontier and interactive trade-off analysis process. In this paper, the features of the IET analyses are investigated in detail. Graphical and analytical methods and procedures are explored for generating and analysing data envelopes and efficient frontiers for multiple input and multiple output DEA models using the DEA-IMRP approach. This computational investigation generates useful insights into the JET analyses and leads to the definition of new efficiency measures, which are instrumental to help conduct trade-off analysis for setting realistic performance targets. A numerical example is studied to illustrate the findings graphically. A case study for UK retail banks is conducted using the new methods and procedures investigated in this paper. (C) 2011 Elsevier Ltd. All rights reserved.
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