Multi-criteria decision aid approach for the selection of the best compromise management scheme for ELVs: the case of Cyprus

Each alternative scheme for treating a vehicle at its end of life has its own consequences from a social, environmental, economic and technical point of view. Furthermore, the criteria used to determine these consequences are often contradictory and not equally important. In the presence of multiple conflicting criteria, an optimal alternative scheme never exists. A multiple-criteria decision aid (MCDA) method to aid the Decision Maker (DM) in selecting the best compromise scheme for the management of End-of-Life Vehicles (ELVs) is presented in this paper. The constitution of a set of alternatives schemes, the selection of a list of relevant criteria to evaluate these alternative schemes and the choice of an appropriate management system are also analyzed in this framework. The proposed procedure relies on the PROMETHEE method which belongs to the well-known family of multiple criteria outranking methods. For this purpose, level, linear and Gaussian functions are used as preference functions.     

基于AHP-TOPSIS方法的儿童安全座椅设计方案评价研究

目的 解决儿童安全座椅设计方案评价过程中的主观性和片面性等问题,获得科学的设计方案。方法 依据文献研究和用户与专家问卷找出消费者选购产品时考虑的需求点和问题点,初选出儿童安全座椅评价指标;采用合理性测评筛除低效用指标,确定儿童安全座椅评价指标体系的科学构建。提出一种结合层次分析法（AHP）和逼近理想解排序法（TOPSIS）的综合评价方法,对3款儿童安全座椅的设计方案进行综合评价优选,确定第2种设计方案为获得分数最高的优选方案。结论 AHP-TOPSIS模型应用于儿童安全座椅设计方案的优选可以消减决策者对设计方案评价的片面性与主观性,实现相对科学的儿童安全座椅设计方案的评价。该方法在其他产品开发过程中处于设计阶段的方案评价与优选具有一定的通用性。     

A methodological concept for phase change material selection based on multiple criteria decision analysis with and without fuzzy environment

Selection of proper phase change material (PCM) plays an important role towards the development of a latent heat thermal energy storage system. Selection of the phase change material is a difficult and restrained task due to the immense number of different available materials having different characteristics. One has to select such PCM which will give the desired thermal performance at minimum cost. This study deals with two Multiple Attribute Decision-Making (MADM) methods to solve PCM selection problem. These two methods are technique for order preference by similarity to ideal solution (TOPSIS) method and fuzzy TOPSIS method that uses linguistic variable presentation and fuzzy operation. Both the methods use an analytic hierarchy process (AHP) method to determine weights of the criteria. TOPSIS and fuzzy TOPSIS methods are used to obtain final ranking. A problem to evaluate the best choice of PCM used in solar domestic hot water system is considered here to demonstrate the effectiveness and feasibility of the proposed model. Empirical results showed that the proposed methods are viable approaches in solving PCM selection problem. TOPSIS is suitable for the use of precise performance ratings while the fuzzy TOPSIS is a preferred technique when the performance ratings are vague and inaccurate.     

Multicriteria decision-aid approach for product end-of-life alternative selection

The selection of the best compromise alternative for treating a product at its end of life (EOL) is presented. Each EOL alternative has its own consequences from an economical, environmental and social point of view. The criteria used to determine these consequences are often contradictory and not equally important. In the presence of multiple conflicting criteria, an optimal EOL alternative rarely exists. Hence, the decision-maker should seek the best compromise EOL alternative. The present paper proposes a multicriteria decision-aid (MCDA) approach to aid the decision-maker in selecting the best compromise EOL alternative on the basis of his/her preferences and the performances of EOL alternatives with respect to the relevant environmental, social and economic criteria. This approach is important because it allows the user to consider various conflicting criteria simultaneously and it takes into account his/her preferences. The paper analyses the most important aspects of this approach such as the constitution of a set of EOL alternatives, the selection of a list of relevant criteria to evaluate the EOL alternatives and the choice of an appropriate multicriteria decision-aid method. A case study is provided to illustrate how the proposed approach can be used for product EOL alternative selection in real-world applications.     

Application of stochastic analytic hierarchy process for evaluating algal cultivation systems for sustainable biofuel production

Algal biomass is considered as a promising source of alternative fuel energy given its high yield per land area and other potential benefits. Categorized as an advanced generation biofuel feedstock, microalgae are grown in non-conventional ways through different cultivation systems. A preference of a cultivation system may vary depending on a given scenario and its inherent configuration (strength and weakness). Hence, the usage of a specific cultivation system to sustainably produce algal biofuels depends on various factors. Thus, a multi-criteria approach based on analytic hierarchy process (AHP) is proposed for evaluating alternative cultivation systems for sustainable production of algal biofuels. The main criteria considered to evaluate the alternatives based on consultation with a panel of expert and from literature are environmental impact, energy consumption, economic viability, social acceptability, and system robustness. Sub-criteria were identified under each main criterion to further qualify the analysis into relevant sub-factors in the sustainable production of algal biofuels. Three cultivations systems were used as an example to demonstrate the developed decision model using qualitative data and quantitative data. Probabilistic scenarios were analyzed using stochastic approach via Monte Carlo simulation. The results of the stochastic-based AHP showed which cultivation system is preferred for conservative (risk-averse) and optimistic (risk-inclined) scenarios.     

An integrated fuzzy approach for the selection of outsourcing manufacturing partners in pharmaceutical R&D

The selection of the outsourcing manufacturing partners (OMPs) is an important issue for research and development (R&D) in the pharmaceutical industry. The selection process considers several main criteria, as well as a few sub-criteria for each main criterion. Such problems can be formulated as hierarchical structures and can usually be resolved with multi-criteria decision-making approaches. This paper presents an integrated fuzzy approach for selecting a suitable OMP in pharmaceutical R&D. In the integrated approach, fuzzy concepts are used for decision-makers’ subjective judgments to reflect the vague nature of the selection process. Fuzzy AHP and fuzzy TOPSIS are included in the integrated approach. Fuzzy AHP is used to determine the fuzzy weights of criteria and sub-criteria because it can effectively determine various criteria's weights in a hierarchical structure. Fuzzy TOPSIS aims to find the OMP with the best performance with respect to the sub-criteria. We exemplify the integrated approach using a numerical application to demonstrate its feasibility.     

Selection of an optimal refinement condition to achieve maximum tensile properties of Al–15%Mg2Si composite based on TOPSIS method

Recently, in situ Al–Mg₂Si composites have been introduced as a new group of particulate metal matrix composites which contain hard particles of Mg₂Si in Al-matrix. Unfortunately, coarsening of Mg₂Si particles deteriorates the mechanical properties so that it is an important obstacle for the wide application of this type of composites. Our previous investigations depicted that the addition of Na and Mn as alloying elements and solution treatment in the different range of temperature can refine Al–Mg₂Si composite structure and improve tensile properties. Selection of the optimal refinement condition to achieve maximum tensile properties of Al–15%Mg₂Si composite is a multiple attribute decision making (MADM) problem where some criteria must be considered in decision making. In present research, technique for order preference by similarity to ideal solution (TOPSIS) and fuzzy TOPSIS methods were employed in solving the case study problem. Weights of each criterion were determined by using an analytic hierarchy process (AHP) method in both TOPSIS and fuzzy TOPSIS methods. The obtained results showed that the employed methods were suitable approaches in solving case study problem. Empirical findings in this study represented that TOPSIS and fuzzy TOPSIS methods might lead to the choice of refined Al–15%Mg₂Si via solution treatment at 450 °C as the preferred alternative.     

A selection of material using a novel type decision-making method: Preference selection index method

The aim of the current study is to implement a novel tool to help the decision-maker for selection of a proper material that will meet all the requirements of the design engineers. Preference selection index (PSI) method is a novel tool to select best alternative from given alternatives without deciding relative importance between attributes. In the present study, three different types of material selection problems are examined. A validation and consistency test of preference selection index method is performed in present work by comparing results of PSI method with published results of graph theory and matrix approach (GTMA), and technique for order preference by similarity to ideal solution (TOPSIS) method, respectively. The research has concluded that the PSI method is logical and more appropriate for the material selection problems.     

模糊理想解法在多准则群决策中的应用

将模糊数学理论引入到不确定环境下的多准则群决策问题中,利用模糊理想解法进行方案排序.用三角模糊数来描述模糊准则权重和模糊准则属性值,给出了使用模糊理想解法进行群决策问题求解的一般步骤;通过供应商选择这一实例验证了本方法的有效性.     

A hybrid approach to machine-tool selection through AHP and simulation

The selection process of a machine tool has been a critical issue for companies for years, because the improper selection of a machine tool might cause many problems having a negative effect on productivity, precision, flexibility, and a company's responsive manufacturing capabilities. Therefore, in this paper, to determine the best machine tool satisfying the needs and expectations of a manufacturing organization among a set of possible alternatives in the market, a hybrid approach is proposed, which integrates an analytic hierarchy process (AHP) with simulation techniques. The AHP as one of the most commonly used multiple criteria decision-making methods is used to narrow down all possible machine tool alternatives in the market by eliminating those whose scores (or weights) are smaller than a determined value obtained under certain circumstances. Then, a simulation generator is used first to automatically model a manufacturing organization, where the ultimate machine tool will be used, and second to try each alternative remaining from the AHP as a scenario on the generated model. Finally, the final alternative is selected by using the unit investment cost ratio, which is calculated by dividing the investment cost per year of each alternative by the additional number of produced units obtained from the simulation experiment of the relevant alternative.     

Optimization on tribological properties of aramid fibre and CaSO4 whisker reinforced non-metallic friction material with analytic hierarchy process and preference ranking organization method for enrichment evaluations

This paper develops an evaluation method based on the analytic hierarchy process (AHP) and preference ranking organization method for enrichment evaluations (PROMETHEE) in order to select the optimal material according to several criteria which are probably conflicting. The material formulations, which were non-metallic friction material modified with aramid fibre and CaSO₄ whisker by different weight, were designed based on the quasi-level uniform method and the friction test results in three typical conditions were considered as criteria for the performance assessment. By AHP, the subjective judgments of evaluators are quantified as the weight for each criterion, while PROMETHEE is employed to determine the complete ranking of the alternatives. Moreover, further results can be obtained from the application of geometrical analysis for interactive assistance (GAIA). The results show that the formula of 70 wt.% NBR modified PF with 12 wt.% CaSO₄ whisker and 4 wt.% aramid fibre exhibits the optimal properties.     

An integrated approach to evaluating conceptual design alternatives in a new product development environment

As many companies have demonstrated over time, a conceptual design for a new product contributes greatly to an improvement in competitiveness, because it permits a reduction of costs, an increase in quality, and, often, a shortening of the time necessary to get the product on the market. That is why the evaluation of conceptual design alternatives created in a new product development (NPD) environment has long been very vital and a critical point for the future success of companies in fast-growing markets. These alternatives can be evaluated using the analytic hierarchy process (AHP), one of the most commonly used multiple criteria decision making (MCDM) techniques. This technique is used to reduce the number of conceptual design alternatives after ranking them using the scores obtained from the process. Furthermore, another technique, simulation analysis integrated with the AHP, is also used to help decision makers (product engineers or managers) perform economic analyses of the AHP's high-score alternatives using data from the generated simulation model of a real-life manufacturing system in which the final alternative is produced. In short, the objectives of this research are: first, to use the AHP technique to evaluate conceptual design alternatives in a NPD environment; second, to use a simulation generator integrated with this technique in order to perform economic analyses for the AHP's high-score alternatives. Finally, the results of both techniques, simulation and AHP, are used in a benefit/cost (B/C) analysis to reach a final decision on the conceptual design alternatives.     

An integration of a hybrid modified TOPSIS with a PGP model for the supplier selection with interdependent criteria

This paper deals with the supplier selection process when the criteria of selection are not independent. The primary aim is to illustrate that ignoring the interdependencies among these criteria leads to an unrealistic decision. Since supplier selection is a multiple-criteria decision-making (MCDM) process, the general structures of the relative methods are outlined in this paper. The proposed methodology then presents a comprehensive approach to find the best ranking among the alternative suppliers of a typical product. A hybrid modified TOPSIS is integrated with a preemptive goal programming model in this study and then compared to an analytical hierarchy process (AHP) to show the effect of considering interdependencies in the supplier selection process. The results indicate that the proposed methodology provides a higher total value of purchasing (TVP) than AHP while the total cost of purchasing (TCP) of both methods are equal. Empirical proof is offered based on a case study.     

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.     

Evaluating flexible manufacturing systems using a combined multiple attribute decision making method

This paper presents a logical procedure to evaluate alternative flexible manufacturing systems for a given industrial application. The procedure is based on a combined multiple attribute decision making method using TOPSIS and AHP methods together. A ‘flexible manufacturing system suitability index’ is proposed that evaluates and ranks flexible manufacturing systems for the given industrial application. The methodology is illustrated by means of an example.     

Team Member Perceptions of Alternative Decision Analysis Approaches

This research evaluated team members’ perceptions of alternative decision analysis approaches when they were asked to analyze a simple or complex data set under a time constraint. There has been significant work done to understand what criteria should be included in this class of problems. However, less work has been done examining the selection of a specific decision analysis approach. This is an area of concern since research has shown that selecting a different decision analysis approach can change the results even when the same data is analyzed. This research effort is a preliminary look at perceptions of alternative decision analysis approaches. A mixed method study analyzing quantitative and qualitative data was completed. Teams were assigned to use one of five different decision analysis approaches, including Weighted Sum, SMART, TOPSIS, AHP, and ELECTRE I. After applying the approach to either a simple or complex data set, team members were surveyed to determine perceptions including comfort with the approach, its results, and ease/difficulty of explaining the approach to coworkers. Discussions were also held with team members to gain additional insights. The study indicated that team members preferred less technically challenging decision analysis approaches, such as Weighted Sum and to a lesser degree SMART, when they were using a simple data set because they found the approach easier to use and to explain to others. The more technically challenging decision analysis approaches, such as AHP and ELECTRE I, were preferred with a complex data set because they provided better insight into the problem. Teams in this study did selected different alternatives when they used different decision analysis approaches. Demographic data was also collected but was not found to influence results in this study.     

An integrated approach for machine tool selection using fuzzy analytical hierarchy process and grey relational analysis

Selecting a proper machine tool is one of the important decisions a company has to make. Companies which fail to do so face many problems which negatively affect the firm's productivity, flexibility, precision and its responsiveness capabilities. Selection of a machine tool involves a lot of criteria to be simultaneously studied and so it requires a multi-criterion decision making (MCDM) method to solve it. Also the subjectivity involved in such decisions ask for the use of theories such as fuzzy and grey which are very effective in handling subjective inputs. This paper integrates the fuzzy analytic hierarchy process (AHP) and grey relational analysis approaches for the selection of a machine tool from a given set of alternatives. Fuzzy AHP is used to calculate the priority weights of the criteria. Subsequently grey relational analysis (GRA) is employed to rank the alternatives. A well known problem existing in literature has been picked up for the numerical illustration. The results obtained in this paper are better when compared with that existing in literature.     

Using a QCAC–Entropy–TOPSIS approach to measure quality characteristics and rank improvement priorities for all substandard quality characteristics

A key issue faced within the manufacturing industry is determining how to measure quality characteristics and prioritise improvements to be made to all substandard quality characteristics of a product with respect to resource requirements and performance improvement potential. This study proposes a QCAC–Entropy–TOPSIS approach in order to address this issue. It combines the Quality Characteristic Analysis Chart (QCAC), entropy method and Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS). The proposed method is not only helpful to measure and determine whether the quality characteristics meet 6σ, 5σ, 4σ or 3σ but also to rank improvements in all substandard quality characteristics of a product in light of resource requirements and potential for performance improvements simultaneously, making it suitable to all manufacturing industries. Moreover, it also can be a powerful tool for analysing the problems that lead to substandard quality characteristics due to poor accuracy and/or precision. Firstly, using the QCAC, the substandard quality characteristics of the product can be determined and the corresponding values of the Discrimination Distance (DD) can then be computed. Subsequently, all the substandard quality characteristics can be regarded as alternatives when conducting entropy and TOPSIS analyses. Secondly, the weights of the evaluation criteria can be calculated by using the entropy method. Lastly, the weights of the evaluation criteria and the values of DD can be substituted into the TOPSIS method. The manufacturer can then categorically prioritise improvement options for all substandard quality characteristics with respect to resource requirements, and consider potential for performance improvements simultaneously. An example is provided for a bicycle quick release manufacturer to illustrate in detail the calculation process of the developed approach. Finally, the advantages of the proposed method are also given through comparisons with Process Capability Analysis Chart and TOPSIS methods.     

An integrated fuzzy multi-criteria group decision-making approach for green supplier evaluation

Purchasing is one of the most vital functions within a company and supplier performance evaluation is one of the most important business processes of the purchasing function. Traditionally, companies have considered factors such as price, quality, flexibility, etc. while evaluating suppliers. However, environmental pressures urge them to consider green issues. This study proposes a decision model for supplier performance evaluation by considering various environmental performance criteria. An integrated, fuzzy group decision-making approach is adopted to evaluate green supplier alternatives. More precisely, a fuzzy analytic hierarchy process (AHP) is applied to determine the relative weights of the evaluation criteria and an axiomatic design (AD)-based fuzzy group decision-making approach is applied to rank the green suppliers. Finally, a case study is given to demonstrate the potential of the methodology.