Using TODIM to evaluate green supply chain practices under uncertainty

This study approaches the problem of exploring the importance and performance levels in green supply chain practices (GSCP) under conditions of uncertainty. This contribution creates a mechanism that assists in the process of analyzing and selecting the alternatives aligned with the proposed criteria on both the qualitative and quantitative scales. This analysis uses the acronym from the interactive and multi-criteria decision-making method (known as TODIM in Portuguese), a discrete multi-criteria method based on prospect theory. However, the criteria weights and alternatives are described as linguistic preferences and involve quantitative data. The qualitative preferences transformed into crisp values and the quantitative data converts into comparable scale. The results indicate the discrepancies between the importance and performance levels of the GSCP. This study identified set of principal criteria that can influence the recommendations for strategic direction in the most systematic and wide-ranging manner.     

Stochastic multicriteria acceptability analysis using the data envelopment model

Data envelopment analysis (DEA) and stochastic multicriteria acceptability analysis (SMAA-2) are methods for evaluating alternatives based on multiple criteria. While DEA is mainly an ex-post tool used for classifying alternatives into efficient and inefficient ones, SMAA-2 is an ex-ante tool for supporting multiple criteria decision-making. Both methods use a kind of value function where the importance of criteria is modeled using weights. Unlike many other methods, neither DEA nor SMAA-2 requires decision-makers’ weights as input. Instead, these so-called non-parametric methods explore the weight space in order to identify weights favorable for each alternative. This paper introduces the SMAA-D method, which is a combination of DEA and SMAA-2. SMAA-D can be characterized as an extension of DEA to handle uncertain or imprecise data to provide stochastic efficiency measures. Alternatively, the combined method can be seen as a variant of SMAA-2 with a DEA-type value function.     

On setting scale efficient targets in DEA

This paper discusses theoretical and practical aspects of setting scale efficient targets in DEA. We provide new models for setting scale efficient targets for overall inefficient DMUs which overcome some of the technical problems in the commonly used methods of setting a target. The new targets are shown to be the same under input minimisation and output maximisation criteria. Practical problems of implementing the targets can be addressed by an entirely different approach which is also considered.     

Geometrical representations for MCDA

In this paper geometrical representations for multicriteria decision problems are proposed. This new approach provides assistance to understand the conflictual aspects of the criteria and to tackle the problem of the weights associated to them. A generalized criterion, including a preference function, is first generated for each criterion. This allows to define unicriterion preference flows for which a geometrical representation can be obtained by using the Principal Components Analysis. The actions are represented by points and criteria by axes in the PCA plane. A decision axis taking into account the weights associated to the criteria can be defined. This technique provides the decision-maker with a considerable enrichment for the understanding of his problem: clusters of actions can be considered, the importance of the criteria can be evaluated, conflictual criteria are immediately detected, incomparability between actions is emphasized and explained, best compromise actions are easily selected, new decision-axes representing possible clusters of criteria can be considered, undesirable actions can be eliminated, … The technique consists in a powerful new qualitative decision tool. It is illustrated in the paper on some examples treated by the Promethee I and II methods. A didactic and user-friendly microcomputer code is available.     

Graph-based multi-agent decision making

In lots of practical multi-criteria decision making (MCDM) problems, there exist various and changeable relations among the criteria which cannot be handled well by means of the existing methods. Considering that graphic or netlike structures can be used to describe the relationships among several individuals, we first introduce the graphic structure into MCDM and formalize the relations among criteria. Then, we develop a new tool, called graph-based multi-agent decision making (GMADM) model, to deal with a kind of MCDM problems with the interrelated criteria. In the model, the graphic structure is paid sufficient attention to in two main aspects: (1) how the graphic structure has influence on the benefits of agents (or the criteria values); and (2) the relation between the graphic structure and the importance weights of agents (criteria). In this case, we can select the best plan(s) (or alternative(s)) according to the overall benefits (the overall criteria values) resulting from the model. Moreover, a fuzzy graph-based multi-agent decision making (FGMADM) method is developed to solve a common kind of situations where the graphic structure of agents is uncertain (confidential or false). Three examples are used to illustrate the feasibility of these two developed methods.     

A method for determining the weights of criteria: The centralized weights

In multicriteria analysis many methods use weights to represent the relative importance of criteria. The noncompensatory aggregation procedure used in outranking methods enables comparisons of subsets of criteria from this point of view. An interactive method is presented, which requests only ordinal comparisons from the decision maker. The relation ‘more important than’ is assumed to be a semiorder. Therefore, the indifference part of this relation is not necessarily transitive. The judgements can be formulated as linear inequalities, which constrain the set of feasible weights and threshold values. All vertices of this polyhedron are determined, the threshold and the unknown real weights are estimated by the centroid. Some characteristics, a possible refinement in the estimation and an illustrative example are also given.     

Bayesian inference and life testing plans for generalized exponential distribution

Recently generalized exponential distribution has received considerable attentions. In this paper, we deal with the Bayesian inference of the unknown parameters of the progressively censored generalized exponential distribution. It is assumed that the scale and the shape parameters have independent gamma priors. The Bayes estimates of the unknown parameters cannot be obtained in the closed form. Lindley’s approximation and importance sampling technique have been suggested to compute the approximate Bayes estimates. Markov Chain Monte Carlo method has been used to compute the approximate Bayes estimates and also to construct the highest posterior density credible intervals. We also provide different criteria to compare two different sampling schemes and hence to find the optimal sampling schemes. It is observed that finding the optimum censoring procedure is a computationally expensive process. And we have recommended to use the sub-optimal censoring procedure, which can be obtained very easily. Monte Carlo simulations are performed to compare the performances of the different methods and one data analysis has been performed for illustrative purposes. This work was partially supported by a grant from the Department of Science and Technology, Government of India     

Oscillation of Third-order Delay Dynamic Equations on Time Scales

This paper is concerned with the oscillatory behavior of a class of third-order noonlinear variable delay neutral functional dynamic equations on time scale. By using the generalized Riccati transformation and inequality technique, we establish some new oscilla- tion criteria for the equations. Our results extend and improve some known results, but also unify the oscillation of third-order nonlinear variable delay functional differential equations and functional difference equations with a nonlinear neutral term. Some examples are given to illustrate the importance of our results.     

Duality for Algebraic Linear Programming

A duality theory for algebraic linear (integer) programming (ALP) is developed which is of the same importance for linear (integer) programming with linear algebraic objectives as linear programming duality is for classical LP. In particular, optimality criteria for primal, primal-dual, and dual methods are given which generalize feasibility and complementarity criteria of classical LP. Strong duality results are given for special combinatorial problems. Further, the validity and finiteness of a primal simplex method based on a feasibility criterion are proved in the case of nondiscrete variables. In this case a strong duality result is shown.     

Mean utility in the assurance region model

This paper addresses the problem of ranking a finite set of alternatives through a linear utility with coefficients randomly distributed. In order to model relative importance of the different criteria, assurance regions on weights are used. A closed formula for the expected utility of each alternative is obtained under uniformity assumptions, and as a consequence, different ranking methods are proposed.     

From vicious to virtuous circles: problem structuring for quantified decision making in operationalization of corporate social responsibility

There is no formalised approach for problem structuring and quantitative decision support to operationalise corporate social responsibility (CSR) implementation. In this paper, techniques for considering criteria relationships are outlined and a holistic, systematic framework combining a qualitative and quantitative method for practical CSR integration is provided. Cognitive mapping (CM) is applied to structure the problem picture, and the cause–effect relationships between decision elements. Soft CM methodology is employed to assess the cross-criteria interactions, at both an individual and a collective level. The interactions of criteria can have a significant impact upon CSR implementation. Such impacts can be direct or indirect through their close linkages to other criteria. The causal strategic map serves as an input to the analytic network process (ANP) to carry out the multi-criteria decision analysis. Then, CM and ANP are applied in a comparative analysis to verify whether the measures of criteria significance do correspond. The key criteria in networks are identified using centrality in CM and single limited priorities in ANP. This study demonstrates that using criteria without considering their interactions will result in shortcomings in the evaluation and assessment of CSR programmes. The holistic framework, combining CM and ANP proposed in this work, enhances the process of problem structuring and supports preference-based evaluation of decision alternatives. The results of our study yield that the mapping procedure has an influence on the criteria significance in networks. The correspondence between CM and ANP is stronger when cause relationships are rigidly interpreted. More unambiguous interpretations of causal relations can be achieved if methods are used jointly and common peaks of importance in both CM and ANP could potentially serve as indications of key decision elements.     

Robust and neutral methods for aggregating preferences into an outranking relation

Definitions are proposed for the concepts of robustness and neutrality of a decision-aid method. They are illustrated on the problem of aggregating preferences into an outranking relation in the presence of an importance relation on the criteria. We show that the concepts allow the analyst to better understand how the methods are grounded and provide him with arguments to justify the choice of one method instead of another.     

A new system for weighting environmental criteria for use within ELECTRE III

ELECTRE III is a multi-criteria decision-aid model, particularly suited to the environmental appraisal of complex engineering projects. The authors propose a system which can be used to weight criteria within those non-compensatory decision-aid models, such as ELECTRE III, where information on the relative importance of the criteria is required. The limitations of the weighting systems used to date within ELECTRE III are outlined, and Hinkle's `resistance to change' grid is proposed as a new, simple, and straightforward weighting system with a coherent methodological basis. A worked example of Hinkle's technique, applied in the area of solid waste management, illustrates how it can be used to derive importance weightings for a set of mainly environmental criteria.     

一类分支过程的收敛性

随机稳定性是各种随机模型中的至关重要的问题,随机稳定性中的关键问题是找出过程遍历,指数遍历和强遍历的准则．该文对一类重要的分支过程给出了过程指数遍历及强遍历的条件．在证明中主要应用了几种不同的比较方法,从该文的结果可以看出,这种方法是有效的,因而在其它情形中也是非常有意义的．而且所得结果的概率意义也是十分清楚的．     

A characterization of concordance relations

The notion of concordance is central to many multiple criteria techniques relying on ordinal information, e.g. outranking methods. It leads to compare alternatives by pairs on the basis of a comparison of coalitions of attributes in terms of “importance”. This paper proposes a characterization of the binary relations that can be obtained using such comparisons within a general framework for conjoint measurement that allows for intransitive preferences. We show that such relations are mainly characterized by the very rough differentiation of preference differences that they induce on each attribute.     

Extended use of the cards procedure as a simple elicitation technique for MAVT. Application to public procurement in Switzerland

The cards procedure was designed in the early 90 as a simple way to elicit weights for multiple criteria decision analysis outranking methods. It is based on the elicitation of the difference of importance between successive pairs of criteria. We propose to extend its use in two directions:     

基于标度理论的股指时间序列相似性分析

股指时间序列的相似性分析是当前金融学研究的热点之一。为了提高股指时间序列相似性分析的准确度,从标度不变性、多重分形及波动聚集性三个层面定义了标度理论的度量指标,并基于此对股指序列进行表示。将分割后的每一序列子区间看作时间点,则分割、表示后的不同股指序列构成一个多指标的面板数据。基于面板数据特征及指标相对重要性,提出了一种新型的多指标面板数据相似性度量函数——复合距离函数,用以度量股指时间序列的相似性。聚类结果表明,相较于其他两种方法,基于标度理论和复合距离函数的相似性度量方法能够显著提高相似性度量的准确度,同时具有较强的稳健性。     

Deriving weights in multiple-criteria decision making with support vector machines

A key problem in Multiple-Criteria Decision Making is how to measure the importance of the different criteria when just a partial preference relation among actions is given. In this note we address the problem of constructing a linear score function (and thus how to associate weights of importance to the criteria) when a binary relation comparing actions and partial information (relative importance) on the criteria are given. It is shown that these tasks can be done viaSupport Vector Machines, an increasingly popular Data Mining technique, which reduces the search of the weights to the resolution of (a series of) nonlinear convex optimization problems with linear constraints. An interactive method is then presented and illustrated by solving a multiple-objective 0–1 knapsack problem. Extensions to the case in which data are imprecise (given by intervals) or intransitivities in strict preferences exist are outlined.     

Criteria and dimension reduction of linear multiple criteria optimization problems

Two of the main approaches in multiple criteria optimization are optimization over the efficient set and utility function program. These are nonconvex optimization problems in which local optima can be different from global optima. Existing global optimization methods for solving such problems can only work well for problems of moderate dimensions. In this article, we propose some ways to reduce the number of criteria and the dimension of a linear multiple criteria optimization problem. By the concept of so-called representative and extreme criteria, which is motivated by the concept of redundant (or nonessential) objective functions of Gal and Leberling, we can reduce the number of criteria without altering the set of efficient solutions. Furthermore, by using linear independent criteria, the linear multiple criteria optimization problem under consideration can be transformed into an equivalent linear multiple criteria optimization problem in the space of linear independent criteria. This equivalence is understood in a sense that efficient solutions of each problem can be derived from efficient solutions of the other by some affine transformation. As a result, such criteria and dimension reduction techniques could help to increase the efficiency of existing algorithms and to develop new methods for handling global optimization problems arisen from multiple objective optimization.