An extreme-distance approach to multiple criteria ranking

A distance approach based on extreme points, or predefined ideal and anti-ideal points, is proposed to improve on the TOPSIS (Technique for Order Performance [or Ordered Preference] by Similarity to Ideal Solution) method of multiple criteria ranking. Two case studies demonstrate how the analysis procedure works, and provide a basis for comparison of the proposed method to the original TOPSIS and similar methods. In applications, the new method produces results that are generally consistent with the original technique, but offers new features such as a clear interpretation of extreme points, more flexibility in setting extreme points, no normalization distortion, and the ability to handle non-monotonic criteria.     

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.     

An approach for optimization of robot-generated rigid-body interpolation using dynamic criteria

The present paper describes an approach for generating spatial trajectories in multibody systems including rigid–body rotations such that dynamic criteria such as forces, accelerations, velocities, etc. as well as limiting restrictions for the motion–generating mechanical device, e.g., a robot, can be considered. The task is to find a rigid–body interpolation that fulfills optimality criteria at the target trajectory as well as in the mechanical system. Application of general optimization methods fails due to the difficulty of finding feasible initial guesses that will converge. The present approach proposes to decouple the general problem into two stages, a first stage in which a pure trajectory optimization is carried out without regard of the mechanical system, and a second stage in which the carrying mechanical system is incorporated. The trajectory planning involves the use of splines of 5–th order as well as an SQP optimization for determining the spline support points as design variables. The approach is illustrated for the example of the generalized waiter problem. (© 2008 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim)     

An innovative orders-of-magnitude approach to AHP-based mutli-criteria decision making: Prioritizing divergent intangible humane acts

An innovative Analytic Hierarchy Process-based structure is developed to capture the relationship between various levels of activities contributed by people to society. Physical objects have widespread extension and degrees of importance that often differ by many orders of magnitude. Similarly, mental thoughts and criteria occur in widely heterogeneous entities that have to be sorted and arranged into homogeneous groups of few elements in each group so that one can evaluate the relationships among them accurately, from the smallest to the largest. It is through such a framework for organizing factors with smooth transition that it is possible to derive reliable priorities from expert judgments. The proposed model enables one to make decisions and allocate resources in as detailed and fine a way as possible. In addition to the traditional approach of structuring criteria into multiple clusters, the alternatives of a decision are also organized into the lowest multiple levels of that hierarchy. This arrangement and evaluation of alternatives differs from one criterion to another, which adds to the complexity of the undertaking when the alternatives are heterogeneous. The coherent approach to structuring complex decisions with the Analytic Hierarchy Process enables one to transcend the complexity of dealing in a scientific way with the problem of widespread orders of magnitude of criteria and alternatives in a complex decision. When the magnitudes are actually very small or very large, the accuracy of ratingalternativesoneatatime instead of comparing them in pairs involves much guessing, and can lead to a questionable outcome. Alternatively, comparisons, which are necessary for the measurement of intangibles, have greater and better justified accuracy.     

On weighting two criteria with a parameter in combinatorial optimization problems

Two criteria in a combinatorial problem are often combined in a weighted sum objective using a weighting parameter between 0 and 1. For special problem types, e.g., when one of the criteria is a bottleneck value, efficient algorithms are known that solve for a given value of the weighting parameter.     

An introduction and survey of the evidential reasoning approach for multiple criteria decision analysis

The Evidential Reasoning (ER) approach is a general approach for analyzing multiple criteria decision problems under various types of uncertainty using a unified framework—belief structure. In this paper, the ER approach is surveyed from two aspects: theoretical development and applications. After a brief outline of its development and extension over a twenty year period, the ER approach is outlined with a focus on the links among its various developments. Future research directions in the area are also explored in the survey.     

A semi-free weighting matrices approach for neutral-type delayed neural networks

In this paper, a new approach is proposed for stability issues of neutral-type neural networks (DNNs) with constant delay. First, the semi-free weighting matrices are proposed and used instead of the known free weighting matrices to express the relationship between the terms in the Leibniz–Newton formula to simplify the system synthesis and to obtain less computation demand. Second, global exponential stability conditions which are less conservative and restrictive than the known results are derived. At the same time, based on the above approach, fewer variable matrices are introduced in the construction of the Lyapunov functional and augmented Lyapunov functional. Two examples are given to show their effectiveness and advantages over others.     

基于FCM-组合赋权的难采储量分类

目前储量的分类标准是通过划分指标值的范围来确定的,这就要求所有指标值恰好符合既定的指标范围,否则难以划分储量类别。为克服这一问题,本文结合模糊c-均值算法和组合赋权法实现难采储量的分类。首先基于效益指标运用模糊c-均值算法自动搜索储量的最佳类别,再利用主客观赋权偏差最小的思想,构建组合赋权模型,确定属性指标的权重,并计算储量效益指标值,结合模糊c-均值结果判别难采储量类别。最后以大庆某油田为实例,对其难采储量进行了分类,有效指导难采储量滚动开发决策。     

Auctions,public tenders,and fair division games: An axiomatic approach

Auctions, public tenders, and fair division games are considered as special classes of games with incomplete information. The specialty of these games is that choosing a strategy in such a game amounts to displaying (the not necessarily true) preferences. Our main axiom of displayed envy-freeness states that according to his displayed preferences no player should prefer another player's net trade to his own. This axiom and the well-known property of incentive compatibility imply the rules of auctions and public tenders which are originally discussed by Vickrey. We consider our axiomatic characterization as a strong support for the Vickrey-rules. There is no obvious reason why the actually applied rules (e.g. the rules of public tenders in the Federal Republic of Germany) do often violate these rules.For fair division problems the two axioms are shown to be mutually inconsistent. By weakening the requirement of incentive compatibility we, nevertheless, can determine rules for fair division problems which are a reasonable analogue of the Vickrey-rules. Finally, it is discussed how our ideas can be extended to other allocation problems.     

A multiple criteria decision-making approach for the selection of stocks

A fundamental principle of modern portfolio theory is that portfolio selectiondecisions are generally made using two criteria, corresponding to the first twomoments of return distributions, namely the expected returnportfolio variance.One criticism over this theory, which has often been addressed both bypractitioners and academics, is that it fails to embody all thedecision-maker's objectives, through the various stages of the decisionprocess. The aim of this paper is to present an alternative methodologicalapproach for modeling one of the most crucial phases of the portfolio managementprocess, the security selection phase. The main characteristic of the proposedapproach is that it fully takes into account the inherent multi-dimensionalnature of the problem, although allowing the decision-maker to incorporate hispreferences in the decision process. The validity of the proposed approach istested through an illustrative application in Athens Stock Exchange. Besides, adetailed categorized bibliography is provided, relative to the application ofthe techniques of multiple criteria decision making to the problems and issuesof portfolio management.     

A general approach for optimizing regular criteria in the job-shop scheduling problem

Even though a very large number of solution methods has been developed for the job-shop scheduling problem, a majority has been designed for the makespan criterion. In this paper, we propose a general approach for optimizing any regular criterion in the job-shop scheduling problem. The approach is a local search method that uses a disjunctive graph model and neighborhoods generated by swapping critical arcs. The connectivity property of the neighborhood structure is proved and a novel efficient method for evaluating moves is presented. Besides its generality, another prominent advantage of the proposed approach is its simple implementation that only requires to tune the range of one parameter. Extensive computational experiments carried out on various criteria (makespan, total weighted flow time, total weighted tardiness, weighted sum of tardy jobs, maximum tardiness) show the efficiency of the proposed approach. Best results were obtained for some problem instances taken from the literature.     

Coincidence criteria for maximal stable bridges in two game problems of approach

We consider a finite-dimensional conflict-controlled system whose behavior on a finite time interval is described by a vector differential equation. We analyze two game problems of approach in the phase space. In both problems the same terminal set is considered: in the first case, one should guarantee that the phase vector of the system reaches the terminal set at the final instant of time; in the second case, the phase vector should reach the terminal set no later than the final time instant. It is natural to assume that the construction of a solution to the first problem is much simpler than the construction of a solution to the second problem; this fact is confirmed by available experience. The paper is devoted to finding conditions on the system and the terminal set under which the solutions to the above problems coincide. Using these conditions, one can replace the solution of the second problem by the simpler solution of the first problem.     

An adaptive weighting parameter estimation between local and global intensity fitting energy for image segmentation

Local and global intensity fitting energy are widely used for image segmentation. In order to improve the segmentation quality in the presence of intensity inhomogeneity, in this paper, we propose a new adaptive rule for obtaining weighting parameter estimation between the local and global intensity fitting energy. Following the minimization of the energy functional, the value of the weighting parameter is dynamically updated with the contour evolution, which is effective and accurate for extracting the object.     

An improved method for ranking alternatives in multiple criteria decision analysis

Scoring rules are an important disputable subject in data envelopment analysis (DEA). Various organizations use voting systems whose main object is to rank alternatives. In these methods, the ranks of alternatives are obtained by their associated weights. The method for determining the ranks of alternatives by their weights is an important issue. This problem has been the subject at hand of some authors. We suggest a three-stage method for the ranking of alternatives. In the first stage, the rank position of each alternative is computed based on the best and worst weights in the optimistic and pessimistic cases, respectively. The vector of weights obtained in the first stage is not a singleton. Hence, to deal with this problem, a secondary goal is used in the second stage. In the third stage of our method, the ranks of the alternatives approach the optimistic or pessimistic case. It is mentionable that the model proposed in the third stage is a multi-criteria decision making (MCDM) model and there are several methods for solving it; we use the weighted sum method in this paper. The model is solved by mixed integer programming. Also, we obtain an interval for the rank of each alternative. We present two models on the basis of the average of ranks in the optimistic and pessimistic cases. The aim of these models is to compute the rank by common weights.     

A Bayesian approach for multiple criteria decision making with applications in Design for Six Sigma

Linking end-customer preferences with variables controlled at a manufacturing plant is a main idea behind popular Design for Six Sigma management techniques. Multiple criteria decision making (MCDM) approaches can be used for such purposes, but in these techniques the decision-maker's (DM) utility function, if modelled explicitly, is considered known with certainty once assessed. Here, a new algorithm is proposed to solve a MCDM problem with applications to Design for Six Sigma based on a Bayesian methodology. At a first stage, it is assumed that there are process responses that are functions of certain controllable factors or regressors. This relation is modelled based on experimental data. At a second stage, the utility function of one or more DMs or customers is described in a statistical model as a function of the process responses, based on surveys. This step considers the uncertainty in the utility function(s) explicitly. The methodology presented then maximizes the probability that the DM's or customer's utility is greater than some given lower bound with respect to the controllable factors of the first stage. Both stages are modelled with Bayesian regression techniques. The advantages of using the Bayesian approach as opposed to traditional methods are highlighted.     

Selecting and weighting features using a genetic algorithm in a case-based reasoning approach to personnel rostering

Personnel rostering problems are highly constrained resource allocation problems. Human rostering experts have many years of experience in making rostering decisions which reflect their individual goals and objectives. We present a novel method for capturing nurse rostering decisions and adapting them to solve new problems using the Case-Based Reasoning (CBR) paradigm. This method stores examples of previously encountered constraint violations and the operations that were used to repair them. The violations are represented as vectors of feature values. We investigate the problem of selecting and weighting features so as to improve the performance of the case-based reasoning approach. A genetic algorithm is developed for off-line feature selection and weighting using the complex data types needed to represent real-world nurse rostering problems. This approach significantly improves the accuracy of the CBR method and reduces the number of features that need to be stored for each problem. The relative importance of different features is also determined, providing an insight into the nature of expert decision making in personnel rostering.     

An efficient and simple model for multiple criteria supplier selection problem

Simply looking for vendors offering the lowest prices is not “efficient sourcing” any more. Selection of suppliers is a multiple criteria decision. We propose a weighted linear program for the multi-criteria supplier selection problem. In addition to mathematical formulation, this paper studies a transformation technique which enables our proposed model to be solved without an optimizer. The model for multi-criteria supplier selection problem can be easily implemented with a spreadsheet package. The model can be widely applied to practical situations and does not require the user with any optimization background.