The facility location problem from the perspective of triple bottom line accounting of sustainability

Design of facilities network, allocation of customers to be served from the facilities and their operations have strong economic, environmental and social impacts. Although the decisions in the facility location problem may have varying effects on these impacts, simultaneous consideration of these effects in the early stages of decision-making for facility location selection and network plan has attracted limited attention in the facility location decision literature. Specifically, the social dimension and mathematical modelling are rarely used. In this paper, we present a decision support framework for the facility location problem that incorporates the triple bottom line accounting of sustainability. The framework is a valuable integration of mathematical modelling embedding the criteria with proper measurement indicators in a multi-objective model, perspectives of the related stakeholders, any thresholds and assumption, model analysis, and the decision-maker strategy to find the best-fit alternative. We demonstrate our methodological approach to establish a supply network for digital products in Turkey using real data. The results indicate that the method can balance the economic, environmental and social pillars, based on limitations of the three pillars and strategic perspective of the decision-maker. The decision-maker can interpret the interactions among the three pillars of sustainability and can make his decision by analysing the balance between them.     

An aggregation technique for optimal decision-making in materials selection

Materials selection is an onerous but very important activity in the design process. An inappropriate choice of material(s) can adversely affect the productivity and profitability and hence reputation of a manufacturing organization. The complexity of materials selection makes multi-criteria analysis an invaluable tool in the engineering design process. However, the application of various multi-criteria decision making (MCDM) methods can yield different results, especially when alternatives lead to similar performance. Therefore, an aggregation technique is proposed in this paper for optimal decision-making. In this approach, ranking orders obtained by various MCDM methods are used as the input of the suggested procedure and the outputs are aggregation rankings, which help designers and engineers to reach a consensus on materials selection for a specific application. An illustrative example is given to demonstrate the application of this procedure and its effectiveness in obtaining optimal materials selection.     

Materials selection using complex proportional assessment and evaluation of mixed data methods

Material selection is a very fast growing multi-criteria decision-making (MCDM) problem involving a large number of factors influencing the selection process. Proper choice of material is a critical issue for the success and competitiveness of the manufacturing organizations in the global market. Selection of the most appropriate material for a particular engineering application is a time consuming and expensive process where several candidate materials available in the market are taken into consideration as the tentative alternatives. Although a large number of mathematical approaches is now available to evaluate, select and rank the alternative materials for a given engineering application, this paper explores the applicability and capability of two almost new MCDM methods, i.e. complex proportional assessment (COPRAS) and evaluation of mixed data (EVAMIX) methods for materials selection. These two methods are used to rank the alternative materials, for which several requirements are considered simultaneously. Two illustrative examples are cited which prove that these two MCDM methods can be effectively applied to solve the real time material selection problems. In each example, a list of all the possible choices from the best to the worst suitable materials is obtained which almost match with the rankings as derived by the past researchers.     

A Fuzzy AHP and PROMETHEE method-based heuristic for disassembly line balancing problems

Nowadays, new products have been introduced in the market at an ever increasing pace due to rapid technology advancement. Consequently, products are becoming outdated and discarded faster than ever before. Since the demand for new solutions to economically deal with such outdated products begun to rise, the disassembly line has emerged as a viable solution to this problem. The disassembly line has been considered as a viable choice for automated disassembly of returned products. The problem of sequence generation in disassembly is complex due to its NP-Hard nature and therefore the heuristically solutions are most preferable for these types of problems. In this paper, a heuristic has been proposed to assign the disassembly tasks/parts to the work stations under its precedence constraints. It incorporates Fuzzy analytic hierarchy process (Fuzzy AHP) and PROMETHEE method for the selection of tasks for assignment to the disassembly line. The Fuzzy AHP has been used to find the relative importance of each criteria and PROMETHEE method has been used for prioritising the tasks for assignment. The proposed heuristics has been illustrated with an example and the results have been compared to the heuristic proposed by McGovern and Gupta. The proposed heuristic performs well and has shown improvements in terms of cycle time and idle time of the workstations.     

A linguistic risk prioritization approach for failure mode and effects analysis: A case study of medical product development

Failure mode and effects analysis (FMEA) is a widely used risk management technique for identifying the potential failures from a system, design, or process and determining the most serious ones for risk reduction. Nonetheless, the traditional FMEA method has been criticized for having many deficiencies. Further, in the real world, FMEA team members are usually bounded rationality, and thus, their psychological behaviors should be considered. In response, this study presents a novel risk priority model for FMEA by using interval two‐tuple linguistic variables and an integrated multicriteria decision‐making (MCDM) method. The interval two‐tuple linguistic variables are used to capture FMEA team members' diverse assessments on the risk of failure modes and the weights of risk factors. An integrated MCDM method based on regret theory and TODIM (an acronym in Portuguese for interactive MCDM) is developed to prioritize failure modes taking experts' psychological behaviors into account. Finally, an illustrative example regarding medical product development is included to verify the feasibility and effectiveness of the proposed FMEA. By comparing with other existing methods, the proposed linguistic FMEA approach is shown to be more advantageous in ranking failure modes under the uncertain and complex environment.     

Material selection for the tool holder working under hard milling conditions using different multi criteria decision making methods

Nowadays machining of materials in their hardened state, also called hard machining, is a challenge in production of tools and molds. It has some advantages such as lower process time and lower manufacturing cost when compared to conventional machining. In machining of hard workpiece materials, however, very high stresses act on the tool holder through the cutting tool. These stresses necessitate the tool holder to have some specific properties. Especially in hard milling, the tool holder should have high stiffness and should be able to dissipate the energy generated during interrupted cutting. Material cost of the tool holder is also important since lower costs provide a competitive advantage for manufacturers. The material selection for the tool holder should be conducted considering aforementioned requirements. To tackle the difficulty of the material selection with specific properties from a large number of alternatives, multi-criteria decision-making (MCDM) methods have been used. In this paper a decision model including extended PROMETHEE II (EXPROM2) (preference ranking organization method for enrichment evaluation), TOPSIS (technique for order performance by similarity to ideal solution) and VIKOR (VIšekriterijumsko KOmpromisno Rangiranje) methods were used for the selection of the best material for the tool holder used in hard milling. The criteria weighting was performed by compromised weighting method composed of AHP (analytic hierarchy process) and Entropy methods. The candidate materials were ranked by using these methods and the results obtained by each method were compared. It was confirmed that MCDM methods can be used for the solution of real time material selection problems. Tungsten carbide–cobalt and Fe–5Cr–Mo–V aircraft steel were found as the best materials for the tool holder production. The obtained results are found to be rather satisfactory and can be used in design stage of hard machining operations.     

考虑消费者预期后悔的零售商策略选择

建立随机需求下的两阶段销售模型,研究消费者高价后悔和缺货后悔对零售商定价与库存决策的影响,分析两种运营策略：价格承诺和快速响应。结果表明,高价(缺货)后悔加重(减轻)消费者策略性等待行为,零售商应降低(提高)定价并减少(增加)库存;价格承诺和快速响应均能缓解消费者策略性等待行为,但两者的价值受消费者预期后悔的影响相反;价格承诺仅在补货成本高于某个阈值且消费者预期后悔敏感度低于某个阈值时优于快速响应。     

Treatment and recycling system optimisation with activity-based costing in WEEE reverse logistics management: an environmental supply chain perspective

Waste electrical and electronic equipment (WEEE) reverse logistics management has increasingly received much attention in recent years not only because of the fast increase of WEEE but also the legislations in many developed countries. This paper focuses on the treatment and recycling system, and proposes a two-stage multi-objective decision framework. In the treatment stage, the responsible producer selects treatment suppliers under extended producer responsibility by a pre-emptive goal programming model. After the wastes are depolluted and transformed to recyclable materials, the process enters the recycling stage in which the decision-maker plans the reclaimed material production by a linear programming model for profit maximisation. An illustrative case study is presented, and the sensitivity analyses show that the ranking of suppliers is more stable than the quantities allocated to suppliers under different priority structures, so ranking of suppliers should also be given attention in such multi-objective decision-making. In addition, a decision model with environmental constraints can reduce the production of the products that have more environmental impacts.     

Practical common weight multi-criteria decision-making approach with an improved discriminating power for technology selection

A practical common weight multi-criteria decision-making (MCDM) methodology with an improved discriminating power for technology selection is introduced. The proposed MCDM methodology enables the evaluation of the relative efficiency of decision-making units (DMUs) with respect to multiple outputs and a single exact input. Its robustness and discriminating power are illustrated via a previously reported robot evaluation problem by comparing the ranking obtained by the proposed MCDM framework with that obtained by the cross-efficiency analysis, which is a well-known data envelopment analysis-based methodology. The results indicate that the proposed methodology enables further ranking of data envelopment analysis-efficient DMUs with a notable saving in computations compared with cross-efficiency analysis. Finally, the proposed MCDM framework is extended to incorporate ordinal as well as exact outputs, and an application is presented to illustrate the methodology.     

Emotions and foreign direct investment: A theoretical and empirical exploration

Abstract

Emotions are largely absent in economic models. Possibly for this reason, many theories fail to explain the actual decisions made by managers.

Therefore, we integrate emotions with regular microeconomic theory. We focus on FDI decisions, and include both economic and emotional variables in our analysis of the firm’s decision-making process.

In our theoretical analysis, emotions are included in a utility maximization model that considers not only the utility of the firm but also the utility of the individual decision-maker.

In our empirical analysis, the presence of emotions in FDI decision-making is tested using a sample of Dutch enterprises that considered an investment in Central or Eastern Europe between 1990 and 2000.

     

A multicriteria approach to timeout collaboration protocol

This paper presents a multicriteria approach to exploring the properties of timeout collaboration protocol with different timeout thresholds in general testing environments. This is formulated as a discrete multiple criteria optimisation problem by choosing five representative timeout thresholds as alternatives with five common performance measures of production systems. The PROMETHEE method is adopted to deal with this multicriteria problem. The divide-and-label algorithm is developed to rank all the alternatives with the overall intensity of their performance, by using multiple valued outranking graphs from the PROMETHEE with multiple replications. It is shown that two extreme timeout thresholds, T ₀ = 0 and ∞, are efficient over multiple criteria in almost all cases. The divide-and-label algorithm is a very efficient approach to overcome the limitations of the PROMETHEE algorithm and Belz and Mertens's procedure with multiple criteria and replications.     

Fuzzy Multi-criteria Decision Making for Decision Support in Port CapacityUpgrade

In many port capacity upgrade projects, choosing a supplier of equipment is a complicated decision, project managers must consider many criteria to choose a supplier to ensure the project is completed on time, optimal in terms of benefit and cost. Therefore, selecting the equipment supplier in this project is a multi-criteria decision-making process. The multi-criteria decision-making (MCDM) model is applied in many fields to select the optimal solution, but there are very few studies using the MCDM model to support project managers in evaluating and selecting optimal solutions in port capacity upgrade project. In this research, the authors combine Fuzzy Analytic Network Process model and Weighted Aggregated Sum Product Assessment concepts to develop a decision support system in port capacity upgrade project. The scientific and practical contribution of this study is to successfully propose a decision support model in a fuzzy environment. The results of the study will be a useful guideline to assist decision makers in port capacity upgrading projects in Taiwan as well as in other countries around the world.     

Fuzzy α-discounting method for multi-criteria decision-making

The α-Discounting Method was developed to be an alternative to and extension of the Analytical Hierarchy Process (AHP) to solve multi-criteria decision-making (MCDM) problems with non-commensurable and conflicting criteria. In contrast to the AHP, this method works not only for pairwise comparisons but also for n-wise comparisons if relative importance of criteria can be expressed in a system of linear homogenous equations. This method also has a comparative advantage as it can transform those MCDM problems, classified as inconsistent by the AHP, into a consistent form. This study briefly compares the two methods and then develops the Fuzzy α-Discounting Method for Multi-Criteria Decision Making (Fα-DM MCDM). Two illustrative fuzzy MCDM problems from the literature have been solved to show how the Fα-DM MCDM works.     

Material selection using PROMETHEE combined with analytic network process under hybrid environment

Material selection involves a great number of attributes, including quantitative and qualitative ones, among which there exist dependences of various degrees, and so belongs to multi-attribute decision making problem (MADM) under hybrid environment in the presence of interdependences. The method of preference ranking organization method for enrichment evaluations (PROMETHEE) combined with analytic network process (ANP) is presented to select the best material for a given application, where ANP is used to identify weights, and PROMETHEE to rank alternatives. Taking the material selection for a journal bearing as example, the decision-making procedure is enunciated, first determining the attributes according to the failure analysis and the requirements of customers, then screening out the feasible solutions, and last fixing the optimal solution, Aluminum bronze, which is in conformity with practice test. Finally, the method of expediting the calculation process is presented developing graphical user interface-based (GUI-based) related software.     

Application of analytical network process for the evaluation of sustainable business practices in an Indian relays manufacturing organization

Sustainable business strategies or technologies determine the market dynamism so as to withstand competitiveness. The evaluation of such strategies is a multi-criteria decision making (MCDM) problem. To deal with such problems, analytical hierarchy process (AHP) and analytical network process (ANP) could be deployed. AHP considers the distribution of goal amongst the elements being compared and judges the element which has the greater influence on the goal. In order to overcome the drawbacks with AHP, ANP could be used which is a holistic approach in which all attributes and alternatives involved are connected in a network system that accepts dependencies. Priorities which are established in ANP are the same way as they are in the AHP using pair wise comparisons and judgments. ANP is the most comprehensive framework for the analysis of societal, governmental and corporate decisions that are available today to the decision-maker. It is a process that allows one to include all the factors and criteria, tangible and intangible that has an effect on making a best decision. The paper reports a research study that is focused on the selection of the best alternative from the perspective of sustainability for an Indian relays manufacturing organization.     

Maintenance policy selection in manufacturing firms using the fuzzy MCDM approach

In manufacturing firms, there is a critical need for proper maintenance of manufacturing facilities. The maintenance process enhances customer satisfaction and reliability of the products, and increases the profit of the manufacturer. Therefore, a proper maintenance policy selection is a critical issue for manufacturers, as an inefficient maintenance policy affects not only the direct cost of the firm but also the other aspects. In the present study, maintenance policy selection at the level of the firm rather than the equipment level is shown, and for selection various criteria have been identified. The presented work not only provides the best alternatives but also provides an alternative ranking, which facilitates decision-makers in choosing alternatives according to their constraints. These selection criteria are different in nature, as some give a crisp value, whereas others are defined in linguistic terms. To select the appropriate maintenance policy, a distance-based fuzzy multicriteria decision-making (MCDM) approach has been employed. The proposed method provides the means for integrating the economic figure of merit with the strategic performance variables. The MCDM approach is efficient in incorporating data, in the form of linguistic variables, triangular fuzzy numbers, and crisp numbers, into the evaluation process of maintenance policy alternatives. A comprehensive example illustrates the application of the distance-based fuzzy MCDM approach.     

Challenges of human–machine collaboration in risky decision-making

The purpose of this paper is to delineate the research challenges of human–machine collaboration in risky decision-making. Technological advances in machine intelligence have enabled a growing number of applications in human–machine collaborative decision-making. Therefore, it is desirable to achieve superior performance by fully leveraging human and machine capabilities. In risky decision-making, a human decision-maker is vulnerable to cognitive biases when judging the possible outcomes of a risky event, whereas a machine decision-maker cannot handle new and dynamic contexts with incomplete information well. We first summarize features of risky decision-making and possible biases of human decision-makers therein. Then, we argue the necessity and urgency of advancing human–machine collaboration in risky decision-making. Afterward, we review the literature on human–machine collaboration in a general decision context, from the perspectives of human–machine organization, relationship, and collaboration. Lastly, we propose challenges of enhancing human–machine communication and teamwork in risky decision-making, followed by future research avenues.     

New Decision-Making Technique Based on Hurwicz Criteria forFuzzyRanking

Efficient decision-making remains an open challenge in the research community, and many researchers are working to improve accuracy through the use of various computational techniques. In this case, the fuzzification and defuzzification processes can be very useful. Defuzzification is an effective process to get a single number from the output of a fuzzy set. Considering defuzzification as a center point of this research paper, to analyze and understand the effect of different types of vehicles according to their performance. In this paper, the multi-criteria decision-making (MCDM) process under uncertainty and defuzzification is discussed by using the center of the area (COA) or centroid method. Further, to find the best solution, Hurwicz criteria are used on the defuzzified data. A new decision-making technique is proposed using Hurwicz criteria for triangular and trapezoidal fuzzy numbers. The proposed technique considers all types of decision makers’ perspectives such as optimistic, neutral, and pessimistic which is crucial in solving decision-making problems. A simple case study is used to demonstrate and discuss the Centroid Method and Hurwicz Criteria for measuring risk attitudes among decision-makers. The significance of the proposed defuzzification method is demonstrated by comparing it to previous defuzzification procedures with its application.     

Multi-objective microcomputer-based interactive production planning

This paper presents a production-planning methodology which brings about interactions between the decision-maker and the analyst in a situation where multiple objectives are considered. An interactive goal-programming technique is developed in which the decision-maker bases his judgement on pairwiae comparisons of the values of the objective functions at each iteration. Three goals are considered: minimizing production cost, maintaining a balanced workforce level for the periods over the time horizon and last, but not least, minimizing the deviation between the actual production level and that specified by the government. A microcomputer-baaed procedure is adopted and its application to the case of a small diesel engine assembly factory is presented.