Incremental analysis for MCDM with an application to group TOPSIS

The study aims to exploit incremental analysis or marginal analysis to overcome the drawbacks of ratio scales utilized in various multi-criteria or multi-attribute decision making (MCDM/MADM) techniques. In the proposed 11-step procedure, multiple criteria of alternatives are first reorganized as two categories – benefits and costs – and decision information will be manipulated separately. The performances of alternatives are then evaluated on their incremental benefit–cost ratio, and the rank can be obtained by applying the group TOPSIS (technique for order preference by similarity to ideal solution) model (Shih et al., 2007). Two representations of cost, i.e., a cost index and utility index, are proposed in the model to better-fit real-world situations. In addition, some considerations on costs and input–output relations are also discussed in order to understand the essentials of incremental analysis. In the final part, a case of robot selection demonstrates the suggested model to be both robust and efficient in a group decision-making environment.     

三角模糊数去模糊化对VIKOR妥协解的影响研究

针对准则值和准则权重均为三角模糊数的多准则决策问题,研究了不同三角模糊数去模糊化方法适用的数学运算规则,应用VIKOR方法进行三角模糊数去模糊化的必要环节和前提条件,分析了去模糊化对群体效用值和个体遗憾值以及对妥协解的影响机制,给出了一种拓展的VIKOR方法的决策步骤,最后运用算例说明了方法的实施过程和有效性。     

Evaluation and refinement of aspiration-based methods in MCDM

The performance of aspiration-based interactive methods of MCDM is evaluated by means of a simulation model, based on idealized assumptions regarding preferences of the decision maker (DM). It is demonstrated that naive application of these procedures can lead to premature termination of the procedure at relatively poor solutions (i.e. relative to the idealized preferences), leaving much of the decision space unexplored by the DM. This suggests practical steps to build a form of “intelligence” into algorithms for applying aspiration-based methods, to ensure that an improving sequence of solutions is examined, and that early termination is avoided. The simulation studies show that with the implementation of these steps, aspiration-based and value function-based methodologies produce comparable results, with the aspiration-based methods showing greater robustness to violations of preferential independence of the criteria.     

A comparative evaluation of interactive solution methods for multiple objective decision models

This paper describes a laboratory experiment which compares the performance from the user's point of view of four different solution methods for multiple objective decision models with continuous variables. These are the method of Zionts and Wallenius, the surrogate worth tradeoff method, the method of Steuer and Choo and a simplistic ‘naive’ solution method. The users exhibited different preferences among the different solution methods with the method of Steuer and Choo favoured overall. The results highlight a need for solution methods to accommodate the decision making characteristics of the user.     

Stochastic ultimate load analysis:models and solution methods 1

The stochastic ultimate load analysis model used in the safety analysis of engineering structures can be treated as a special case of chance-constrained problems (CCP) which minimize a stochastic cost function subject to some probabilistic constraints. Some special cases (such as a deterministic cost function with probabilistic constraints or deterministic constraints with a random cost function) for ultimate load analysis have airady been investigated by various researchers. In this paper, a generai probabilistic approach to stochastic ultimate load analysis is given. In doing so, some approximation techniques are needed due to the fact that the problems at hand are too complicated to evaluate precisely. We propose two extensions of the SQP method in which the variables appear in the algorithms inexactly. These algorithms are shown to be globally convergent for all models and locally superlinearly convergent for some special cases     

Compromise solutions,domination structures,and Salukvadze's solution

We outline the concepts of compromise solutions and domination structures in such a way that the underlying assumptions and their implications concerning the solution concept suggested by Salukvadze may be clearer. An example is solved to illustrate our discussion.     

Numerical solution of fuzzy Camassa-Holm equation by using Homotopy analysis methods

In this paper, a fuzzy Camassa-Holm equation is solved by using the  homotopy analysis method (HAM). The approximation solution of this equation is calculated in the form of series which its components are computed by applying a recursive relation. The existence and uniqueness of the solution and the convergence of the proposed method are proved.     

A comparative analysis of methods for constructing weak orders from partial orders

This paper compares three methods (sequel, cardinal, maximal) for constructing a weak order from a partial order on a finite set. The constructed weak orders include the partial order. To evaluate the methods, several different selection disciplines were used to stochastically generate partial orders from a fixed linear order. The error of a weak order which includes a generated partial order is a function of the number of ordered pairs added to the partial order to get the weak order which are the reverse of ordered pairs in the fixed linear order. In all cases, the sequel and cardinal mean errors were much lower than the maximal mean error. In most but not all cases, the cardinal mean error was lower than the sequel mean error.     

Capturing decision maker preference: Experimental comparison of decision analysis and MCDM techniques

This paper describes the results of a laboratory study which investigates preference in decision making under certainty with multiple, conflicting objectives and continuous decision variables. Techniques for solving such problems are taken from the fields of decision analysis and optimization: the SMART technique for the former and both the NAIVE and Zionts-Wallenius techniques for the latter. The purpose of the experiment is to determine the ability of each technique to correctly capture decision maker preference. In addition, the relative preference of the decision maker for each technique was obtained. The experiment was conducted on a random sample of business school undergraduates and involved a decision with three criteria. The results give insight into the use of several techniques when confronted with decisions with multiple criteria.     

Consequences of dropping nonessential objectives for the application of MCDM methods

In this article we consider the problem of nonessential objectives for multiobjective optimization problems (MOP) with linear objective functions. In 1977 an approach based on the reduction of size of the matrix of objective functions has been worked out by one of the present authors (Gal, T., Leberling, H., 1977. European Journal of Operations Research 1, 176–184). Although this method for dropping nonessential objectives leads to a mathematically equivalent MOP, problems concerning the application of MOP methods may arise. For instance, dropping some (or all) of the nonessential objectives the question is, how to ensure obtaining the same solution as with all objectives involved. We consider the problem of adapting the parameters of multiobjective optimization methods. For the case of weighting methods a simple procedure for adapting the weights is analyzed. For other methods, e.g. reference point approaches, such a simple possibility for adapting the parameters is not given.     

Portfolio Selection: A Compromise Programming Solution

A surrogate for an investor's bi-criteria utility function (profitability, safety) is proposed as an alternative methodology for selecting portfolios. The optimum is approximated by resorting to a recent utility theorem expounded in multi-criteria analysis. This method is developed for an ‘average’ investor and could be used as a routine procedure by investment consultants with incomplete information of the client's utility function.     

A comparative analysis of two methods of polynomial operator interpolation in a Hilbert space

A comparative analysis of two methods of polynomial operator interpolation is performed. These methods are shown to be equivalent and, in the case of functional spaces, the efficiency of the algorithm for approximation with respect to the number of arithmetic operations is demonstrated. Translated fromObchyslyuval'na ta Prykladna Maternatyka, No. 78, 1994, pp. 49–54.     

多项式回归的建模方法比较研究

在实际工作中,人们在采用回归模型解释因果变量间的相关关系时,经常会遇到自变量之间存在幂乘关系的情况。在这种情况下,多项式回归模型成为一个合理的选择。由于多项式回归模型中自变量之间存在较强的相关关系,采用普通最小二乘回归方法来估计变量的回归系数,则会存在较大的误差。在本文中,为了提高多项式回归模型的预测准确性和可靠性,提出使用主成分分析、偏最小二乘回归建模,并采用仿真数据来比较它们的异同。     

An axiomatic approach to noncompensatory sorting methods in MCDM,II: More than two categories

A number of recent papers have investigated the foundations of methods allowing to sort multi-attributed alternatives between several ordered categories. This paper has a similar objective. Our analysis uses a general conjoint measurement framework, encompassing most sorting models used in MDCM, that was proposed in the literature. Within this framework, we provide an axiomatic analysis of what we call noncompensatory sorting models, with or without veto effects. These noncompensatory sorting models contain the pessimistic version of ELECTRE TRI as a particular case. Our analysis can be seen as an attempt to give a firm axiomatic basis to ELECTRE TRI, while emphasizing its specific feature, i.e., the rather poor information that this model uses on each attribute.     

An axiomatic approach to noncompensatory sorting methods in MCDM,I: The case of two categories

In the literature on MCDM, many methods have been proposed in order to sort alternatives evaluated on several attributes into ordered categories. Most of them were proposed on an ad hoc basis. The purpose of this paper is to contribute to a recent trend of research aiming at giving these methods sound theoretical foundations. Using tools from conjoint measurement, we provide an axiomatic analysis of the partitions of alternatives into two categories that can be obtained using what we call “noncompensatory sorting models”. These models have strong links with the pessimistic version of ELECTRE TRI. Our analysis allows to pinpoint what appears to be the main distinctive features of ELECTRE TRI when compared to other sorting methods. It also gives hints on the various methods that have been proposed to assess the parameters of ELECTRE TRI on the basis of assignment examples.     

Jump-Preserving Regression and Smoothing using Local Linear Fitting: A Compromise

This paper deals with nonparametric estimation of a regression curve, where the estimation method should preserve possible jumps in the curve. At each point x at which one wants to estimate the regression function, the method chooses in an adaptive way among three estimates: a local linear estimate using only datapoints to the left of x, a local linear estimate based on only datapoints to the right of x, and finally a local linear estimate using data in a two-sided neighbourhood around x. The choice among these three estimates is made by looking at differences of the weighted residual mean squares of the three fits. The resulting estimate preserves the jumps well and in addition gives smooth estimates of the continuity parts of the curve. This property of compromise between local smoothing and jump-preserving is what distinguishes our method from most previously proposed methods, that mainly focused on local smoothing and consequently blurred possible jumps, or mainly focused on jump-preserving and hence led to rather noisy estimates in continuity regions of the underlying regression curve. Strong consistency of the estimator is established and its performance is tested via a simulation study. This study also compares the current method with some existing methods. The current method is illustrated in analyzing a real dataset.     

The interval-valued fuzzy TOPSIS method and experimental analysis

The purpose of this paper is to extend the TOPSIS method based on interval-valued fuzzy sets in decision analysis. Hwang and Yoon developed the technique for order preference by similarity to ideal solution (TOPSIS) in 1981. TOPSIS has been widely used to rank the preference order of alternatives and determine the optimal choice. Considering the fact that it is difficult to precisely attach the numerical measures to the relative importance of the attributes and to the impacts of the alternatives on these attributes in some cases, therefore, the TOPSIS method has been extended for interval-valued fuzzy data in this paper. In addition, a comprehensive experimental analysis to observe the interval-valued fuzzy TOPSIS results yielded by different distance measures is presented. A comparative analysis of interval-valued fuzzy TOPSIS rankings from each distance measure is illustrated with discussions on consistency rates, contradiction rates, and average Spearman correlation coefficients. Finally, a second-order regression model is provided to highlight the effects of the number of alternatives, the number of attributes, and distance measures on average Spearmen correlation coefficients.     

Hybrid flexible flowshop problems: Models and solution methods

This paper considers the problem of hybrid flowshop scheduling. First, we review the shortcoming of the available model in the literature. Then, four different mathematical models are developed in form of mixed integer linear programming models. A complete experiment is conducted to compare the models for performance based on the size and computational complexities. Besides the models, the paper proposes a novel hybrid particle swarm optimization algorithm equipped with an acceptance criterion and a local search heuristic. The features provide a fine balance of diversification and intensification capabilities for the algorithm. Using Taguchi method, the algorithm is fine tuned. Then, two numerical experiments are performed to evaluate the performance of the proposed algorithm with three particle swarm optimization algorithms available in the scheduling literature and one well-known iterated local search algorithm in the hybrid flowshop literature. All the results show the high performance of the proposed algorithm.