Multiple Criteria Games-Theory and Applications

After a reivew of basic concepts in multiple criteria optimization, the paper presents a characterization of noncooperative equilibria in multiple criteria games in normal form either by weighted sums or by. order-consistent achievement scalarizing functions, for convex and nonconvex cases. Possible applications of multiple criteria games and such characterizations of their equilibria are indicated. The analysis of multiple criteria games might be especially useful when studying reasons of possible conflict escalation processes and ways of preventing them.

TOPSIS with Belief Structure for Group Belief Multiple Criteria Decision Making

The technique for order performance by similarity to ideal solution （TOPSIS） is one of the major techniques in dealing with multiple criteria decision making （MCDM） problems, and the belief structure （BS） model has been used successfully for uncertain MCDM with incompleteness, impreciseness or ignorance. In this paper, the TOPSIS method with BS model is proposed to solve group belief MCDM problems. Firstly, the group belief MCDM problem is structured as a belief decision matrix in which the judgments of each decision maker are described as BS models, and then the evidential reasoning approach is used for aggregating the multiple decision makers＇ judgments. Subsequently, the positive and negative ideal belief solutions are defined with the principle of TOPSIS. To measure the separation from ideal solutions, the concept and algorithm of belief distance measure are defined, which can be used for comparing the difference between BS models. Finally, the relative closeness and ranking index are calculated for ranking the alternatives. A numerical example is given to illustrate the proposed method.

Dual worth trade-off method and its application for solving multiple criteria decision making problems

To overcome the limitations of the traditional surrogate worth trade-off （SWT） method and solve the multiple criteria decision making problem more efficiently and interactively, a new method labeled dual worth tradeoff （DWT） method is proposed. The DWT method dynamically uses the duality theory related to the multiple criteria decision making problem and analytic hierarchy process technique to obtain the decision maker＇s solution preference information and finally find the satisfactory compromise solution of the decision maker. Through the interactive process between the analyst and the decision maker, trade-off information is solicited and treated properly, the representative subset of efficient solutions and the satisfactory solution to the problem are found. The implementation procedure for the DWT method is presented. The effectiveness and applicability of the DWT method are shown by a practical case study in the field of production scheduling.

A DEA-TOPSIS METHOD FOR MULTIPLE CRITERIA DECISION ANALYSIS IN EMERGENCY MANAGEMENT

A hybrid approach of DEA （data envelopment analysis） and TOPSIS （technique for order performance （preference） by similarity to ideal solution） is proposed for multiple criteria decision analysis in emergency management. Two DEA-based optimization models are constructed to facilitate identifying parameter information regarding criterion weights and quantifying qualitative criteria in TOPSIS. An emergency management case study utilizing data from the Emergency Management Australia （EMA） Disasters Database is provided to demonstrate the feasibility of the proposed analysis procedure.

Regularized multiple criteria linear programs for classification

Although multiple criteria mathematical program （MCMP）, as an alternative method of classification, has been used in various real-life data mining problems, its mathematical structure of solvability is still challengeable. This paper proposes a regularized multiple criteria linear program （RMCLP） for two classes of classification problems. It first adds some regularization terms in the objective function of the known multiple criteria linear program （MCLP） model for possible existence of solution. Then the paper describes the mathematical framework of the solvability. Finally, a series of experimental tests are conducted to illustrate the performance of the proposed RMCLP with the existing methods： MCLP, multiple criteria quadratic program （MCQP）, and support vector machine （SVM）. The results of four publicly available datasets and a real-life credit dataset all show that RMCLP is a competitive method in classification. Furthermore, this paper explores an ordinal RMCLP （ORMCLP） model for ordinal multigroup problems. Comparing ORMCLP with traditional methods such as One-Against-One, One-Against-The rest on large-scale credit card dataset, experimental results show that both ORMCLP and RMCLP perform well.

A method for threshold selection in load extrapolation based on multiple criteria decision-making technology

In order to establish an accurate peak over threshold(POT)model for reasonable load extrapolation,a new threshold selection method based on multiple criteria decision making(MCDM)technology is proposed.The fitting test criterion is taken into consideration in the method.For each candidate threshold,the fitting values of several fitting test criteria are integrated into a comprehensive evaluation value through entropy method and MCDM technology.The threshold corresponding to the minimum comprehensive evaluation value is assumed as the optimal threshold.A random simulation study is carried out to evaluate the performance of the method and to compare them with other literature methods.Genuine load data are applied the proposed method.Both the results shown that the proposed method could be seen as an additional method that complements existing threshold selection methods.

Dynamic multiple criteria group decision-making method based on intuitionistic fuzzy information

In the decision-making process,the decision information provided by decision makers over alter-natives may take the form of intuitionistic fuzzy numbers and come from different periods.The weight of information on decision makers,criteria,periods is usually completely unknown.To this issue,we first utilise hesitation degree information and introduce the concept of confi-dence degree function to determine the decision maker’s weights.Then we aggregate individual evaluation information into group evaluation information through intuitionistic fuzzy number weighted arithmetic averaging operator.We construct a nonlinear optimisation model to gain the criterion weights and apply the aggregate operator to gain the integrated rating value of alternatives in different periods,calculating the deviations of the integrated rating values with respect to their average.Then the period weights are been obtained by using the entropy method.According to the closeness coefficient between alternatives and ideal solution to sort the alternatives and select the optimal one.

Agricultural Investment Project Decisions Based on an Interactive Preference Disaggregation Model Considering Inconsistency

Agricultural investment project selection is a complex multi-criteria decision-making problem,as agricultural projects are easily influenced by various risk factors,and the evaluation information provided by decisionmakers usually involves uncertainty and inconsistency.Existing literature primarily employed direct preference elicitation methods to address such issues,necessitating a great cognitive effort on the part of decision-makers during evaluation,specifically,determining the weights of criteria.In this study,we propose an indirect preference elicitation method,known as a preference disaggregation method,to learn decision-maker preference models fromdecision examples.To enhance evaluation ease,decision-makers merely need to compare pairs of alternatives with which they are familiar,also known as reference alternatives.Probabilistic linguistic preference relations are employed to account for the presence of incomplete and uncertain information in such pairwise comparisons.To address the inconsistency among a group of decision-makers,we develop a pair of 0-1mixed integer programming models that consider both the semantics of linguistic terms and the belief degrees of decision-makers.Finally,we conduct a case study and comparative analysis.Results reveal the effectiveness of the proposed model in solving agricultural investment project selection problems with uncertain and inconsistent decision information.

Extension of Paraconsistent Many-Valued Similarity Method to Group Decision

The Paraconsistent Many-Valued Similarity (PMVS) method for multi-attribute decision making will be incomplete as a decision model if it is not extended to the realm of group decision-making. Therefore, in this article, our primary objective is to show how the paraconsistent many-valued similarity method can be used to solve group decision-making problems involving choice making or ranking of a finite set of decision alternatives. Moreover, since weights are very important parameters in multi-attribute decision-making, we have introduced the Borda rule to calculate the weights of experts and that of every criterion under consideration. To demonstrate how the proposed method works, a numerical example on energy sources of an economy from the points of view of a group of experts is investigated. Further, we compare the results of this new approach with that of fuzzy TOPSIS group decision-making method to illustrate the robustness and effectiveness of the former.

Interval-valued intuitionistic fuzzy aggregation operators

The notion of the interval-valued intuitionistic fuzzy set （IVIFS） is a generalization of that of the Atanassov＇s intuitionistic fuzzy set. The fundamental characteristic of IVIFS is that the values of its membership function and non-membership function are intervals rather than exact numbers. There are various averaging operators defined for IVlFSs. These operators are not monotone with respect to the total order of IVIFS, which is undesirable. This paper shows how such averaging operators can be represented by using additive generators of the product triangular norm, which simplifies and extends the existing constructions. Moreover, two new aggregation operators based on the t.ukasiewicz triangular norm are proposed, which are monotone with respect to the total order of IVIFS. Finally, an application of the interval-valued intuitionistic fuzzy weighted averaging operator is given to multiple criteria decision making.

Robust data envelopment analysis based MCDM with the consideration of uncertain data

The application of data envelopment analysis （DEA） as a multiple criteria decision making （MCDM） technique has been gaining more and more attention in recent research. In the practice of applying DEA approach, the appearance of uncertainties on input and output data of decision making unit （DMU） might make the nominal solution infeasible and lead to the efficiency scores meaningless from practical view. This paper analyzes the impact of data uncertainty on the evaluation results of DEA, and proposes several robust DEA models based on the adaptation of recently developed robust optimization approaches, which would be immune against input and output data uncertainties. The robust DEA models developed are based on input-oriented and outputoriented CCR model, respectively, when the uncertainties appear in output data and input data separately. Furthermore, the robust DEA models could deal with random symmetric uncertainty and unknown-but-bounded uncertainty, in both of which the distributions of the random data entries are permitted to be unknown. The robust DEA models are implemented in a numerical example and the efficiency scores and rankings of these models are compared. The results indicate that the robust DEA approach could be a more reliable method for efficiency evaluation and ranking in MCDM problems.

Integration of Decision－Support and Knowledge－Based Techniques in a Problem－Solving Strategy for Sel

The limitations of traditional approaches to selection problems are examined. A problemsolving strategy is presented in which decision-support and knowledge-based techniques play complementary roles. An approach to the representation of knowledge to support the problem-solving strategy is presented which avoids commitment to a specific programming language or implementation environment. The problem of choosing a home is used to illustrate the representation of knowledge in a specific problem domain. Techniques for implementation of the problem-solving strategy are described. Knowledge elicitation techniques and their implementation in a development shell for application of the problem-solving strategy to any selection problem are also described.

带同类恶化工件机器排序的多用户模型(英文)

We consider a scheduling problem involving a single processor utilized by two customers with constant deteriorating jobs, i.e., jobs whose processing times are an increasing function of their starting times. Traditionally, such scenarios are modeled by assuming that each customer has the same criterion. In practice, this assumption may not hold. Instead of using a single criterion, we examine the implications of minimizing an aggregate scheduling objective function in which jobs belonging to different customers are evaluated with their individual criteria. We examine three basic scheduling criteria： minimizing makespan, minimizing maximum lateness, and minimizing total weighted completion time. We demonstrate all the scheduling problems considered are polynomially solvable.

S-box:six-dimensional compound hyperchaotic map and artificial bee colony algorithm

Being as unique nonlinear components of block ciphers,substitution boxes（S-boxes） directly affect the security of the cryptographic systems.It is important and difficult to design cryptographically strong S-boxes that simultaneously meet with multiple cryptographic criteria such as bijection,non-linearity,strict avalanche criterion（SAC）,bits independence criterion（BIC）,differential probability（DP） and linear probability（LP）.To deal with this problem,a chaotic S-box based on the artificial bee colony algorithm（CSABC） is designed.It uses the S-boxes generated by the six-dimensional compound hyperchaotic map as the initial individuals and employs ABC to improve their performance.In addition,it considers the nonlinearity and differential uniformity as the fitness functions.A series of experiments have been conducted to compare multiple cryptographic criteria of this algorithm with other algorithms.Simulation results show that the new algorithm has cryptographically strong S-box while meeting multiple cryptographic criteria.

Realistic Dilemma and Solution of “Vocational Skill Test” under the Background of Enrollment Reform of Classified Examination in Higher Vocational Colleges in Jilin Province

In the process of Higher Vocational classified examination enrollment reform,Jilin Province has adopted a diversified examination enrollment model and“cultural quality test+vocational skill test”evaluation method,and established the“vocational education college entrance examination”system.This paper analyzes the important role and practical difficulties of“vocational skill test”in Higher Vocational classified examination,studies the existing problems,and puts forward to reasonably divide the proportion of“cultural quality test”and“vocational skill test”,sets diversified admission standards,scientifically sets up the assessment methods and contents of“vocational skill test”,further improves the“cultural quality test+vocational skill test”evaluation method and builds a classified examination and enrollment system more in line with the characteristics of vocational education.

Order Structure Analysis（OSA） for the Optimal Solutions of Multiple Objective Mathematical Programming

In this paper,a variety of solution concepts are trifled into an order structure framework,the concept of the order structure function(OSF) is presented,based on which, a now-type solution for MCDM-OSF-efficient solution or called in this study()-efficient solution,wed efficient solution and strong()-efficient solution,etc.,is proposed. It be been proved that the optimal solution of MCDM or MMP in verious senses,such as the Pareto efficient solution,G-efficient soluition,H-efficient solution,etc.,all can be considered as the special cases of the OSF-efficient solution for the special s and s.Finally,the application of the OSF-efficient solution is discussed.

Application of Transformed Two-Stage Network DEA to Strategic Design of Biofuel Supply Chain Network

This paper proposes an innovative procedure for designing efficient biomass-biofuel logistics networks(BBLNs).This procedure is based on the two-stage network data envelopment analysis(TSN-DEA)models that have been developed to provide specific process guidance for the managers to improve the efficiency of the decision-making unit(DMU)with the TSN process.The crucial issue of the TSN-DEA is that the overall efficiency score depends on the DMUs under evaluation.Thus,the rankings for the DMUs generated by the TSN-DEA model are inconsistent.As a result,the TSN-DEA-based ranking methods are limited.The TSN-DEA’s inconsistency frequently makes it difficult for decision-makers to select the top-rated DMUs.We develop the transformed TSN(T-TSN)DEA method by applying the multi-criteria DEA model to overcome this issue.The proposed method transforms the DMUs with any number of inputs,intermediate measures,and outputs in the TSN process,through the multi-objective programming model with a minimax objective approach,into the DMUs with two inputs and one output in the single-stage network(SSN)process.Then,the well-known DEA methods for the SSN,such as the cross-efficiency and super-efficiency DEA methods,can be applied to evaluate and rank the transformed DMUs more consistently.We exhibit the applicability of the proposed approach for the BBLN design problem.A case study of South Carolina in the USA demonstrates that the proposed method performs well in identifying efficient BBLN schemes more consistently than the traditional TSN-DEA.

An in-depth review of theory of the TOPSIS method:An experimental analysis

Decision-making is an important part of daily and business life for both individuals and organizations.Although the multi-criteria decision-making methods provide decision makers the necessary tools,they have differences in terms of the assumptions and fundamental theory.Hence,selecting the right decision-making method is at least as important as making the decision.TOPSIS(Technique for Order Performance by Similarity to Ideal Solution)method,which is one of the most widely used multi-criteria decision-making methods,has gained attention of researchers and thus various improved versions of the method have been proposed.This study considers the conventional TOPSIS method and experimentally displays the underlying reasons of the lacks of the conventional TOPSIS method by using a simulation technique.Detailed experimental analysis based on simulation with an application is used to reveal theoretical fundamentals of the TOPSIS method to better understand it and contribute to its improvement.

Evaluating the Tourism Resources' Development by AHP

There are a lot of scenic sports and historical sites in China. How to most utilize theseexisting and potential tourism resources is becoming increasingly important in modern time. For solvingthis multiple criteria decision making in a complicated environment in this paper, we will propose aspecific algorithm for evaluating tourism resources’ development and utilization by analytical hierarchyprocess based on experts decision. Generally, we are given solutions by experience of experts to representjudgmental objects. From viewpoint of many experts, in this paper, we will build judgment criteriafor all sub-items. Finally, we developed a systematic, practical, interactive and menu-driven expertdecision support system by foxbase language under the/msdos/Windows environment.

Decision Support System for Evaluating Impact of Product Carbon Labeling Scheme

In this paper a decision support system for systematically evaluating the impact of labeling products with their carbon footprints is developed and applied to prioritize products for carbon labeling in a large supermarket chain in the UK.Carbon labels may change consumers’ behavior and encourage suppliers to implement carbon-reduction solutions.Those changes may,however,lead to unintended risks.To handle the challenges of uncertainties in the evaluation,the Evidential Reasoning approach and the Intelligent Decision System software for multi-criteria decision analysis are applied to support the process.The system developed can be applied to assessing the impact of sustainable development policies to maximize their benefits and minimize their risks.