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Efficiency evaluation of closed-loop supply chains with proportional dual-role measures

Monireh Jahani Sayyad Noveiri, Sohrab Kordrostami, Alireza Amirteimoori (2020)

Kybernetika

Data Envelopment Analysis (DEA) is a beneficial mathematical programming method to measure relative efficiencies. In conventional DEA models, Decision Making Units (DMUs) are usually considered as black boxes. Also, the efficiency of DMUs is evaluated in the presence of the specified inputs and outputs. Nevertheless, in real-world applications, there are situations in which the performance of multi-stage processes like supply chains with forward and reverse flows must be measured such that some...

Estimating the supply chain efficiency loss when the seller has to estimate the buyer’s willingness to pay

Xavier Brusset (2014)

RAIRO - Operations Research - Recherche Opérationnelle

We study the pricing problem between two firms when the manufacturer’s willingness to pay (wtp) for the supplier’s good is not known by the latter. We demonstrate that it is in the interest of the manufacturer to hide this information from the supplier. The precision of the information available to the supplier modifies the rent distribution. The risk of opportunistic behaviour entails a loss of efficiency in the supply chain. The model is extended to the case of a supplier submitting offers to...

Evaluation of decision-making units based on the weight-optimized DEA model

Jiasen Sun, Rui Yang, Xiang Ji, Jie Wu (2017)

Kybernetika

Data envelopment analysis (DEA) is a methodology for measuring best relative efficiencies of a group of peer decision-making units (DMUs) that take multiple inputs to produce multiple outputs. However, the traditional DEA model only aims to maximize the efficiency of the DMU under evaluation. This usually leads to very small weights (even zero weights) being assigned to some inputs or outputs. Correspondingly, these inputs or outputs have little or even no contribution to efficiency, which is unfair...

Extension of reverse elimination method through a dynamic management of the tabu list

Saïd Hanafi, Arnaud Fréville (2001)

RAIRO - Operations Research - Recherche Opérationnelle

The Reverse Elimination Method (REM) is a dynamic strategy for managing the tabu list. It is based on logical interdependencies between the solutions encountered during recent iterations of the search. REM provides both a necessary and sufficient condition to prevent cycling. The purpose of this paper is first to incorporate in REM a chronological order rule when cycling is unavoidable, thereby assuring the finite convergence of Tabu Search. Secondly, we correct a generalization of REM, the so-called...

Extension of Reverse Elimination Method Through a Dynamic Management of the Tabu List

Saïd Hanafi, Arnaud Fréville (2010)

RAIRO - Operations Research

The Reverse Elimination Method (REM) is a dynamic strategy for managing the tabu list. It is based on logical interdependencies between the solutions encountered during recent iterations of the search. REM provides both a necessary and sufficient condition to prevent cycling. The purpose of this paper is first to incorporate in REM a chronological order rule when cycling is unavoidable, thereby assuring the finite convergence of Tabu Search. Secondly, we correct a generalization of REM, the so-called...

Flexible measures in production process: A DEA-based approach

Alireza Amirteimoori, Ali Emrouznejad (2011)

RAIRO - Operations Research

Data envelopment analysis (DEA) has been proven as an excellent data-oriented efficiency analysis method for comparing decision making units (DMUs) with multiple inputs and multiple outputs. In conventional DEA, it is assumed that the status of each measure is clearly known as either input or output. However, in some situations, a performance measure can play input role for some DMUs and output role for others. Cook and Zhu [Eur. J. Oper. Res.180 (2007) 692–699] referred to these variables...

Flexible measures in production process: A DEA-based approach

Alireza Amirteimoori, Ali Emrouznejad (2011)

RAIRO - Operations Research

Data envelopment analysis (DEA) has been proven as an excellent data-oriented efficiency analysis method for comparing decision making units (DMUs) with multiple inputs and multiple outputs. In conventional DEA, it is assumed that the status of each measure is clearly known as either input or output. However, in some situations, a performance measure can play input role for some DMUs and output role for others. Cook and Zhu [Eur. J. Oper. Res.180 (2007) 692–699] referred to these variables...

Forecast horizon and planning horizon paths in time-indexed network

Stanisław Bylka (2006)

Banach Center Publications

The problem of existence of a forecast (or planning) horizon has been considered in many special models, more or less precisely. We specify and investigate this problem for families of cheapest paths in networks with weakly ordered nodes. In a discrete network, the standard forward algorithm finds the subnetwork generated by optimal paths. The proposed forward procedure reduces subnetworks such that the forecast horizon remains unchanged. Based on the final subnetwork, we have an answer to the forecast...

France Telecom workforce scheduling problem: a challenge

Sebastian Pokutta, Gautier Stauffer (2009)

RAIRO - Operations Research

In this paper, we describe the methodology used to tackle France Telecom workforce scheduling problem (the subject of the Roadef Challenge 2007) and we report the results obtained on the different data sets provided for the competition. Since the problem at hand appears to be NP-hard and due to the high dimensions of the instance sets, we use a two-step heuristical approach. We first devise a problem-tailored heuristic that provides good feasible solutions and then we use a meta-heuristic scheme...

Improved interval DEA models with common weight

Jiasen Sun, Yajun Miao, Jie Wu, Lianbiao Cui, Runyang Zhong (2014)

Kybernetika

The traditional data envelopment analysis (DEA) model can evaluate the relative efficiencies of a set of decision making units (DMUs) with exact values. But it cannot handle imprecise data. Imprecise data, for example, can be expressed in the form of the interval data or mixtures of interval data and exact data. In order to solve this problem, this study proposes three new interval DEA models from different points of view. Two examples are presented to illustrate and validate these models.

Interactive compromise hypersphere method and its applications

Sebastian Sitarz (2012)

RAIRO - Operations Research - Recherche Opérationnelle

The paper focuses on multi-criteria problems. It presents the interactive compromise hypersphere method with sensitivity analysis as a decision tool in multi-objective programming problems. The method is based on finding a hypersphere (in the criteria space) which is closest to the set of chosen nondominated solutions. The proposed modifications of the compromise hypersphere method are based on using various metrics and analyzing their influence on the original method. Applications of the proposed...

Interactive compromise hypersphere method and its applications

Sebastian Sitarz (2012)

RAIRO - Operations Research

The paper focuses on multi-criteria problems. It presents the interactive compromise hypersphere method with sensitivity analysis as a decision tool in multi-objective programming problems. The method is based on finding a hypersphere (in the criteria space) which is closest to the set of chosen nondominated solutions. The proposed modifications of the compromise hypersphere method are based on using various metrics and analyzing their influence on the original method. Applications of the proposed...

Currently displaying 61 – 80 of 156