A fuzzy multi-objective programming approach for determination of resilient supply portfolio under supply failure risks

The main contribution of this paper is to develop a new decision tool that interprets strategies for determination of resilient supply portfolio under supply failure risks. The strategic decisions include the allocation of emergency capacities to be pre-positioned at backup suppliers, the output of which can be increased in the event of mitigating a shortage caused by another supplier's failure. The model contains three objective functions – minimising the total cost, minimising the net rejected items and minimising the net late deliveries – while satisfying capacity and minimum order quantity requirement constraints. A weighted additive fuzzy multi-objective model is proposed to simultaneously consider the imprecision of information and the relative importance of objectives for determining the allocation of order quantity and emergency capacity to each supplier. The application of the proposed model is illustrated using an example case of global supply chains with different supplier characteristics.     

Global supplier selection using fuzzy analytic hierarchy process and fuzzy goal programming

Global supplier selection is a multi-goal multi-criteria problem which needs to consider both qualitative and quantitative factors. Which suppliers are the best and how much should be purchased from the selected suppliers is an important purchasing issue for manufacturers. Traditionally, decision makers can determine the best supplier from evaluating few suppliers with qualitative supplier selection criteria by using fuzzy analytic hierarchy process (FAHP), but evaluate dozens of global suppliers simultaneously or determine the order quantity from them will be complex and difficult. Meanwhile, decision makers can determine the order quantity form the suitable suppliers by using fuzzy goal programming (FGP); however, it is not easy to decide weights for each goal of global supplier selection with different supply chain strategies. This study integrated the FAHP and FGP (FAHP-FGP) method to be a new approach for global supplier selection in considering the manufacturer’s supply chain strategies. With FAHP-FGP method, the manufacturer can consistently integrate multi-manager’ opinions in determining weights of each goal and obtain the order quantities for suitable suppliers based on manufacturer’s strategies. To demonstrate the usefulness of the proposed method, a real-world case of a digital consumer products manufacturer is presented.     

基于模糊Borda法的多项目优先级组合评价研究

在构建多项目优先级评定指标体系的基础上,分别运用综合指数法、层次分析法及加权算数平均法三种单一评价模型对项目群中多项目优先级进行评定。通过Spearman等级相关系数对三种方法的一致性进行检验,并基于三种单一评价结果,建立了模糊Borda组合评价模型,对项目群多项目优先级进行了客观、科学地评价。最后引入实例,证明组合评价模型实际可行。     

A group Multi-Criteria Decision-Making method for water supply choice optimization

In this study, an extension of a group Multi-Criteria Decision-Making (MCDM) method based on the fuzzy ELECTRE III (ELimination Et Choice Translating REality) model is presented for water supply choice optimization. The fuzzy ELECTRE III method is improved by using three credibility definitions - concordance, discordance, and net degrees. Experts' opinions are transformed into triangular fuzzy numbers based on the level of uncertainty associated with quantitative and qualitative criteria. The main priority of this method compared to other existing MCDM is that it is a more effective way of dealing with the uncertainties in projects as the application of the opinions is made based on a group decision. A Case Study of a water supply system for the Gamasiab Basin located in the Kermanshah province of Iran is examined to demonstrate the application of the model. Comparing the introduced method's results with the existing MCDMs, including fuzzy TOPSIS and fuzzy AHP methods, indicated that the new method stands more consistent with the local experts' opinions. Therefore, the proposed method is recommended as the optimal decision-making technique for similar applications of complex water supply engineering projects.     

A goal programming approach to public investment decisions: A case study of rural roads in Indonesia

The development planner must often face complex problems with multiple, conflicting objectives. Goal programming provides a general methodology for solving such problems. The tool is applied here to aid in the selection of rural road projects in the Indonesian Rural Works Program. Selection criteria are formalized into a set of nineteen goals which form the basis for a goal programming model. Changes in priority levels of goals and weights are used to analyze the respective effects upon the spatial distribution of investments. The approach is applicable to a wide range of problems and a variety of sensitivity analyses. Despite clear advantages, several drawbacks must be noted. First, the application of the methodology, given its degree of sophistication, is limited to a central decision making unit which has access to appropriate software. Second, the technique assumes that the planner has the ability to formulate alternative actions and consequences in a quantifiable expression.     

A fuzzy AHP approach based on the concept of possibility extent

The main purpose of this paper is to develop a fuzzy AHP method for tackling the uncertainty and imprecision existing in multi-criteria decision process. The proposed method uses fuzzy pair-wise comparison judgments in place of exact numerical values of the comparison ratios. The geometric mean technique is used to integrate all decision-makers’ opinions and construct the fuzzy positive reciprocal matrices. The algebraic operations of triangular fuzzy numbers are utilized to calculate the fuzzy suitability indices of all alternatives. The extent analysis method is used to compute the degree of possibility of priority among fuzzy suitability indices. Besides, two principles are presented to solve the multi-criteria decision problem in a fuzzy decision environment. Principle I provides a partial preorder, and Principle II gives a total preorder on the set of the possible alternatives. Finally, a numerical example of selecting the company with optimal performance in performing customer relationship management is used to demonstrate the decision process of proposed method.     

Determinants of bidder competition in corporate takeovers

The importance of bidder competition in the corporate takeover process has long been recognized in theoretical models. This paper provides empirical tests of those models. The results indicate that resistance by target management to an initial bid encourages multiple bidders. Competing bidders are less likely to enter in cases where the target is large, but more likely to arise when the initial bidder is highly levered. High initial bids (preemptive bids) are found to discourage entry by additional firms. Surprisingly, targets with high levels of free cash flow tend not to be the recipients of multiple bids.     

An extended picture fuzzy multicriteria group decision analysis with different weights: A case study of COVID-19 vaccine allocation

The high contagion rates of COVID-19 and the limited amounts of vaccines forced public health authorities to develop vaccinations strategies for minimizing mortality, avoiding the collapse of health care infrastructure, and reducing their negative impacts to societies and economies. We propose a Multi Criteria Group Decision Making for prioritizing a set of COVID-19 vaccination alternatives, under a picture fuzzy environment, where the weights for Decisions Experts (DE) and criteria are unknown. A panel of six DEs assess six criteria for prioritizing four groups for vaccination. The weights for DE and criteria are handled in the form of fuzzy sets. Three types of weights are calculated: subjective, objective, and mixture weights.According to our results, three out of the six criteria hold 60% of the strategic importance: 1) allocation and distribution, 2) COVID-19 strains and 3) capabilities and infrastructures. However, persons with comorbidities became the group with the highest priority, followed by essential workers, women, and adults older than 40 years. Governments, decision makers, and policy makers can find rigorous scientific evidence for articulating effective vaccinations campaigns from this work, and contribute to minimize undesired outputs, such as high mortality rates or collapse of hospitals.     

A hybrid DEA-MOLP model for public school assessment and closure decision in the City of Philadelphia

Data envelopment analysis (DEA) is generally used to evaluate past performance and multi objective linear programming (MOLP) is often used to plan for future performance goals. In this study, we establish an equivalence relationship between MOLP problems and combined-oriented DEA models using a direction distance function designed to account for desirable and undesirable inputs and outputs together with uncontrollable variables. This equivalence model can be effectively used to support interactive processes and performance measures designed to establish future performance goals while taking into account the preferences of decision makers (DMs). In particular, it allows DMs to consider different efficiency improvement strategies when subject to budgetary restrictions. The applicability of the proposed method and the efficacy of the procedures and algorithms are demonstrated using a case study where the performance of high schools in the City of Philadelphia is evaluated.     

A group decision-making method with fuzzy set theory and genetic algorithms in quality function deployment

Quality function deployment (QFD) has been developed by Toyota Motor Corporation in order to reduce time and shorten design times. QFD is composed of a set of matrices referred to as the house of quality (HOQ). A HOQ matrix can help the cross-functional team to translate customer requirements (CRs) into engineering goals. The importance of CRs and the relationships between CRs and technical characteristics (TCs) are obtained by a group of people with vague and fuzzy decision-making processes in the HOQ. In the conditions, a group decision-making method by using the combination of fuzzy set theory and genetic algorithms (GAs) can be used in QFD to determine the importance of each TC. Besides, a numerical example is illustrated to show that this group decision-making method by using the combination of fuzzy set theory and GAs can be reliably and precisely applied in QFD including TCs at the two-level hierarchy with the consideration of some constraints regarding budget and time limits of TCs for prioritizing TCs to effectively make decisions with fuzziness and ambiguousness.     

Model choice and value-at-risk estimation

Value at risk (VaR) is a commonly used tool to measure market risk. In this paper, we discuss the problems of model choice and VaR performance. The VaRs of daily returns of the Shanghai and Shenzhen indexes are calculated using equally weighted moving average (EQMA), exponentially weighted moving average (EWMA), GARCH(1,1), empirical density estimation method, and the Pareto-type extreme-value distribution methods. Considering the length of the window and the requirement for adequate capital, back testing indicates that the Pareto-type extreme-value distribution method reflects the real market risk more accurately than the other models.     

On a computer-aided systems approach to personnel administration

A systematic evaluation methodology has been developed which integrates some major concepts from value, utility, decision, subjective probability theories and the Delphi method for obtaining a consensus of opinions. These theories are applied to the process of evaluation of personnel for recruitment, promotions, merit raises, transfer, salary administration, training and development. The model requires and utilizes as inputs explicitly stated sets of long-range goals, short-range objectives, resource needs, evaluative criteria, weighting and utility functions, as well as the subjective judgments of appropriate evaluators. The processing of this information may be implemented by manual calculations, batch processing on an IBM 1620 computer, or by direct simulation on a large time-sharing computer system. By utilizing standard statistical procedures and the decision rule to maximize expected utility, the methodology produces the type of output information required for rational decision making.     

模糊层次分析法在基础设施项目融资模式选择中的应用研究

合理地选择项目融资模式对成功完成基础设施项目建设具有重要意义。文章介绍了几种现代流行的基础设施项目融资模式,并对影响融资模式选择的因素进行讨论。考虑到影响因素较多且获取的信息无法用自然语言表达出来,具有模糊性的特点,将层次分析法和模糊决策理论结合起来,建立了项目融资模式选择的模糊层次评价模型,对一个实例进行综合评价排序得出最佳融资模式,为投资者选择合适的基础设施项目融资模式提供一种有效的方法。     

Predicting the failures of prediction markets: A procedure of decision making using classification models

Prediction markets have been an important source of information for decision makers due to their high ex post accuracies. Nevertheless, recent failures of prediction markets remind us of the importance of ex ante assessments of their prediction accuracy. This paper proposes a systematic procedure for decision makers to acquire prediction models which may be used to predict the correctness of winner-take-all markets. We commence with a set of classification models and generate combined models following various rules. We also create artificial records in the training datasets to overcome the imbalanced data issue in classification problems. These models are then empirically trained and tested with a large dataset to see which may best be used to predict the failures of prediction markets. We find that no model can universally outperform others in terms of different performance measures. Despite this, we clearly demonstrate a result of capable models for decision makers based on different decision goals.     

Evaluation of supplier capability and performance: A method for supply base reduction

Development of partnership with suppliers is widely recognised today as a potent tool for supply chain improvement. To develop an effective partnership, it is necessary to have a small supply base and an effort to reduce the supply base to a manageable level. Despite its overwhelming importance, models of supply base reduction are rare. Supplier sorting methods, used for pre-selection of suppliers and sometimes seen as methods for supply base reduction, have limitations ranging from (1) requirement of an exhaustive database of historical information (case-based reasoning), (2) inability to predefine the number of elements in a cluster (cluster analysis) and (3) inability to identify suppliers who are both highly capable as well as high performers (data envelopment analysis). In the present work, we develop a systematic framework for carrying out the supply base reduction process. The study assumes two important dimensions of suppliers—performance and capability. Performance of a supplier represents short-term effects on the achievement of supply chain objectives while supplier capability indicates long-term effects. Many of the performance and capability factors are imprecise in nature. In order to account for the imprecision involved in numerous subjective characteristics of suppliers, we use fuzzy set approach to measure the imprecision of these factors and rank a potential list of suppliers against their performance and capability. We then display their ranks in a ‘capability–performance matrix’ that helps a decision maker arrange the suppliers in decreasing order of preference. The desired numbers of suppliers are finally selected on the basis of this ordered list. The suggested framework will be of immense help to the practising managers in reducing the supply base—a prerequisite for building a strong supplier partnership and developing an effective supply chain.     

直觉梯形模糊几何集成算子及其在群决策中的应用

文章首先定义了直觉梯形模糊数及其运算法则,基于这些运算法则,给出了直觉梯形模糊几何集成算子,即直觉梯形模糊加权几何(IT-WG)算子、直觉梯形模糊有序加权几何(IT-OWG)算子以及直觉梯形模糊混合几何(IT-HG)算子。在此基础上,提出了在属性权重已知的情形下专家评价值以直觉梯形模糊信息给出的多属性群决策方法。最后以产品最优设计方案的选择为实例进行分析,所得结果验证了该方法的有效性。     

基于粗集属性重要性的供应链信息共享的模糊综合评价

供应链信息共享是供应链渠道协调的重要方法，信息共享的程度评价为供应链节点企业的信息共享激励决策以及合作伙伴关系的评估提供重要依据。文章提出了信息共享的评价指标体系．利用评价指标属性的重要性作为权重值，解决了确定权重值的主观性问题。利用粗糙集理论结合模糊数学的有关理论建立了供应链信息共享的综合评价模型并进行了算例分析，为节点企业的激励决策和合作伙伴关系的评价提供依据和理论指导。     

A decision model for regional industrial recruitment and development

Although the practice of industrial recruitment is widespread among regions, its objectives and constraints are neither well established nor carefully evaluated in determining the most desirable industries. As a result, many regions frequently resort to a blind scramble for new industries. This paper suggests a decision model for a regional economy to determine the priority in industrial recruitment. The problem is formulated in terms of a mathematical programming model in which the objectives and constraints are explicitly stated. Regional input-output, table provides additional constraints in the model. The input-output table is also used in testing the economic feasibility of optimal solutions.     

Environmental quality standards: A general equilibrium analysis

The increasing importance of pollution controls as a part of government regulatory activities has motivated considerable concern about the economic impact of these activities. This question is of considerable importance, because environmental quality goals are sometimes in conflict with other objectives such as full employment and economic growth. Policy-makers are thus faced with the task of identifying and measuring the trade-offs between these various objectives. But the measurement of these objectives requires information on their economic impacts. This paper develops a general equilibrium model with pollution specifications which can be used to identify the economic impacts of pollution-control policies. The particular pollution-control policy addressed is an environmental standards approach. The model is based on a technique that combines an explicit representation of consumer demand behaviour vis-à-vis linear aggregate demand functions with activity analysis.     

基于模糊层次分析法的煤炭运输网络多目标优化权重分析研究

煤炭运输网络优化设计的目标是使煤炭运输网络广义费用最小。研究的广义费用由运输费用、延误费用及其权重构成,通过分析煤炭运输网络流量分配目标,运用基于三角模糊数的模糊层次分析法得到各目标权重,进而确定各目标对总目标的贡献大小。