Complex Multi-criteria Decision Research Articles

Study of decision framework of offshore wind power station site selection based on ELECTRE-III under intuitionistic fuzzy environment: A case of China

Offshore wind power projects have been rapidly proposed in China due to policy promotion. Site selection immensely decides the success of any offshore wind power development and is a complex multi-criteria decision making (MCDM) problem. However, canonical MCDM methods tend to fail the site selection process due to the following three problems. Firstly, the compensation problem exists in information processing. Secondly, there exists the problem of incomplete utilization of decision information and information loss in the decision process. Thirdly, the interaction problem in the fuzzy environment is easy to be ignored. To deal with the above problems, this study builds a framework for offshore wind farm site selection decision utilizing Elimination et Choix Traduisant la Realité-III (ELECTRE-III) in the intuitionistic fuzzy environment. First of all, the comprehensive index system of OWPS site selection consisting of veto criteria and evaluation criteria is constructed. Then, the intuitionistic fuzzy set is used in the group decision for the decision makers to express the imperfect knowledge. Moreover, the generalized intuitionistic fuzzy ordered weighted geometric interaction averaging (GIFWGIA) operator is applied to deal with the interaction problem. Together with the likelihood-based valued comparisons, imprecise decision information is reasonably used and information loss problem is rationally avoided. Then a case of China is studied based on the proposed framework, demonstrating the site selection methodology valid and practical. This study implements evaluation method for offshore wind power site selection and also provides a theoretical basis for the development of offshore wind power decision-making in China.

Supply Chain Differentiation: Background, Concept and Examples

The purpose of this paper is to provide new evidence in the field of supply chain differentiation. It aims to combine insights of supply chain management with the service dominant logic to connect fundamental customer requirements with supply chain decision-making. The paper claims to provide a framework that brings together the most relevant factors in the context of supply chain differentiation. The contents of the framework were applied as source to develop a generic decision support flowchart for supply chain executives. From the perspective of “test consumers”—supplemented with secondary data—two cases were examined. The cases provide insights for supply chain differentiation approaches of Adidas and Lego&#174. The crucial factor to link customer requirements with supply chain settings turned out to be the magnitude of customer co-creation along the value chain under consideration of synergies across the channels. The framework provides the opportunity to structure the complex multi-criteria decision problem constituted by supply chain differentiation. The paper provides helpful insights that could be used as starting point for the development of several industry specific decision-finding models or applications in supply chain differentiation.

A TWO-PHASED MULTI-CRITERIA DECISION-MAKING APPROACH FOR SELECTING THE BEST SMARTPHONE

In the last 20 years, rapid and significant developments have occurred in communication and information technologies. In parallel with these developments, the importance of smartphones has increased. In addition, many smartphone manufacturers have launched and continue to launch a number of new models with many features. People who want to buy a new smartphone have difficulties selecting the best smartphone among the numerous models available on the technology markets. Therefore, smartphone selection has become a complex multi-criteria decision-making (MCDM) problem for people. Hence, decision-making processes will be facilitated by using MCDM methods, and these will provide the most appropriate decision. In this paper, the best smartphone among the 28 alternatives determined by the person who will buy them are selected by using three main criteria and 17 sub-criteria with the help of a two-phased MCDM approach. In the first phase, 28 smartphone alternatives are ranked using the analytic network process (ANP). In the second phase, a model that includes the best four alternatives of ANP is created. Afterwards, the best smartphone is selected using the generalised Choquet integral (GCI) method according to this model. Finally, the findings and the results are given.

An Extended PROMETHE II Multi-Criteria Group Decision Making Technique Based on Intuitionistic Fuzzy Logic for Sustainable Energy Planning

The implementations of Preference Ranking Organization Method for Enrichment Evaluation (PROMETHEE) category to complex multi-criteria group decision making (MCGDM) scenarios have been included in thousands areas. Outranking methods such as PROMETHEE II are also greatly employed in energy planning application. In MCGDM methods if decision makers (DMs) are not able to treat precise data in order to define their preferences, the intuitionistic fuzzy set (IFS) theory enables them. IFS attributes are connected with the degree of membership and non-membership, and can be used to draw uncertainty in group decision-making situations. In this paper, a new version of the PROMETHEE II method is proposed, aiming at solving MCGDM problems. Linguistic variables are expressed in the membership function and non-membership function of IFS which are used to assess the weights of all criteria and the ratings of each alternative with respect to each criteria. Conditional normalized Euclidean distance measure is adopted to measure deviations between alternatives on intuitionistic fuzzy set. Then, a ranking algorithm is applied to indicate the order of superiority of alternatives. Finally, a practical example is given to an application of sustainable energy planning to verify our proposed method. Additionally, a comparative analysis is done among the proposed PROMETHEE II method and the intuitionistic fuzzy technique for order preference by similarity to ideal solution (IF-TOPSIS) method and elimination and choice translating reality method (IF-ELECTRE).

CorRECTreatment: a web-based decision support tool for rectal cancer treatment that uses the analytic hierarchy process and decision tree.

The selection of appropriate rectal cancer treatment is a complex multi-criteria decision making process, in which clinical decision support systems might be used to assist and enrich physicians' decision making. The objective of the study was to develop a web-based clinical decision support tool for physicians in the selection of potentially beneficial treatment options for patients with rectal cancer. The updated decision model contained 8 and 10 criteria in the first and second steps respectively. The decision support model, developed in our previous study by combining the Analytic Hierarchy Process (AHP) method which determines the priority of criteria and decision tree that formed using these priorities, was updated and applied to 388 patients data collected retrospectively. Later, a web-based decision support tool named corRECTreatment was developed. The compatibility of the treatment recommendations by the expert opinion and the decision support tool was examined for its consistency. Two surgeons were requested to recommend a treatment and an overall survival value for the treatment among 20 different cases that we selected and turned into a scenario among the most common and rare treatment options in the patient data set. In the AHP analyses of the criteria, it was found that the matrices, generated for both decision steps, were consistent (consistency ratio<0.1). Depending on the decisions of experts, the consistency value for the most frequent cases was found to be 80% for the first decision step and 100% for the second decision step. Similarly, for rare cases consistency was 50% for the first decision step and 80% for the second decision step. The decision model and corRECTreatment, developed by applying these on real patient data, are expected to provide potential users with decision support in rectal cancer treatment processes and facilitate them in making projections about treatment options.

Selecting “The Best” ERP system for SMEs using a combination of ANP and PROMETHEE methods

Enterprise Resource Planning (ERP) system, which integrates all of the units within an organization at the information level, plays an important role for a successful enterprise. With the right ERP system, it is easier to provide coordination between the units, eliminate waste and make faster and better decisions. Adopting an ERP system is a significant investment decision for a firm, therefore a great deal of attention should be given to the selection of the right system. Since there are a large number of criteria to consider in selecting an ERP system, the process itself is regarded as a complex multi-criteria decision making problem. In this study, two prevalent multi-criteria decision making techniques, Analytic Network Process (ANP) and Preference Ranking Organization Method for Enrichment Evaluations (PROMETHEE), are used in combination to better address the ERP selection problem. First, ANP is used to determine the weights of all criteria, and then, the obtained weights are used in the PROMETHEE method for optimal ranking of the alternative system choices. To demonstrate the viability of the proposed methodology, an application case is performed on the ERP selection problem for the Small Medium Enterprises (SMEs) in İstanbul, Turkey. The proposed hybrid methodology successfully ranked the alternatives and identified the best ERP system based on the information obtained from a number of SMEs participated in this study.

A multi-criteria decision-making formulation of trust using fuzzy analytic hierarchy process

Trust models have widespread applications in different areas. In this paper, we formulate trust as a multi-criteria decision-making (MCDM) problem. By applying this new formulation, one can treat the process of trust establishment as a decision-making process based on some set of trustworthiness criteria. By looking at trust as a whole, we may miss some important factors. Only by dividing this concept into its building blocks and weighting those building blocks based on the proposed perception of importance in a context and toward a specific goal, we can achieve a better decision. As a structural way for making trust decisions, the proposed method uses fuzzy analytic hierarchy process (AHP). Fuzzy AHP provides both the advantages of fuzziness, which is compatible with the uncertain, vague, and subjective nature of trust and AHP as a systematic approach to make decisions in complex MCDM problems. In order to aggregate the evaluations of each recommender about every trustee candidate, the Sugeno fuzzy integral is used to build the final trust score. At last, the method calculates the final recommendation score based on the trustor's subjective belief. We present an illustrative example plus an empirical experiment in the context of Web service selection to demonstrate the application of the proposed formulation of trust and the evaluation of trust scores.

A novel hybrid MCDM model based on fuzzy DEMATEL, fuzzy ANP and fuzzy VIKOR for city logistics concept selection

City logistics (CL) tends to increase efficiency and mitigate the negative effects of logistics processes and activities and at the same time to support the sustainable development of urban areas. Accordingly, various measures and initiatives are applying and various conceptual solutions are defining. The effects vary depending on the characteristics of the city. This paper proposes a framework for the selection of the CL concept which would be most appropriate for different participants, stakeholders, and which would comply with attributes of the surroundings. CL participants have different, usually conflicting goals and interests, so it is necessary to define a large number of criteria for concepts evaluation. On the other hand, the importance of the criteria is dependent on the specific situation, i.e., a large number of factors describing the surroundings. In situations like this, selecting the best alternative is a complex multi-criteria decision-making (MCDM) problem consisting of conflicting and uncertain elements. A novel hybrid MCDM model that combines fuzzy Decision Making Trial and Evaluation Laboratory Model (DEMATEL), fuzzy Analytical Network Process (ANP) and fuzzy Višekriterijumska Optimizacija i kompromisno Rešenje (VIKOR) methods is developed in this paper. The model provides support to decision makers (planners, city administration, logistics service providers, users, etc.) when selecting the CL concept, which is successfully performed in this paper for the City of Belgrade.

Multi-Criteria Evaluation Approach of Mobile Text Entry Methods

Current evaluations on mobile text entry methods focus only on speed and accuracy performance but fail to consider subjective preferences of users. Such evaluation is ill-defined and does not constitute a systems approach since it requires a complex multi-criteria decision process that must encompass both objective and subjective criteria. Thus, this paper proposes the use of Analytic Network Process (ANP) in the evaluation of five mobile text entry methods in Android smartphones. A hierarchical network decision problem is developed from a focus group discussion of keen smartphone users. Using ANP, new insights in research and design of text entry methods are proposed. Results show that QWERTY method is the most preferred text entry method and is influenced by criteria on perceived text entry speed and number of keys. A survey is conducted to validate the results of the evaluation process using ANP. The main contribution of this work is in introducing a multi-criteria evaluation approach for mobile text entry research that holistically addresses speed-accuracy performance along with relevant subjective criteria that may potentially influence decision-making.

Supplier Selection Based on FAHP-VIKOR-IVIFs

As the most important part of supply chain management, supplier selection has always received a great deal of attention from practitioners and researchers. However, the nature of supplier selection is a complex multi-criteria decision making (MCDM) problem including many factors which may be in conflict. VIKOR is an efficient method to solve this kind of MCDM problem. But in reality, there usually exists incomplete and uncertain information, and the decision makers cannot easily express their judgments on the alternatives with exact and crisp values. Therefore, a new extended VIKOR method with interval-valued intuitionistic fuzzy sets (IVIF-VIKOR) is proposed in this paper. Then a hybrid MCDM method based on FAHP and the proposed IVIF-VIKOR are used to select supplier under incomplete and uncertain information environment. The feasibility and practicability of FAHP-IVIF-VIKOR method are further manifested through an empirical example.

Seismic induced damageability evaluation of steel buildings: a Fuzzy-TOPSIS method

Seismic resiliency of new buildings has improved over the years due to better seismic codes and design practices. However, there is still large number of vulnerable and seismically deficient buildings. It is not economically feasible to retrofit and upgrade all vulnerable buildings, thus there is a need for rapid screening tool. Many factors contribute to the damageability of buildings; this makes seismic evaluation a complex multi-criteria decision making problem. Many of these factors are noncommensurable and involve subjectivity in evaluation that highlights the use of fuzzy-based method. In this paper, a risk-based framework earlier proposed by Tesfamariam and Saatcioglu (2008a) is extended using Fuzzy-TOPSIS method and applied to develop an evaluation and ranking scheme for steel buildings. The ranking is based on damageability that can help decision makers interpret the results and take appropriate decision actions. Finally, the application of conceptual model is demonstrated through a case study of 1994 Northridge earthquake data on seismic damage of steel buildings.

English

Supplier selection of electricity power generating, transmitting and distributing system is part of problem solving environment in a power utility as it is a long-term investment for the organization. Therefore, the supplier selection decision making directly influences the operational and financial positions of a power utility. In addition, the supplier selection of a power-related system is a complex multi-criteria decision problem. While some criteria may be common across different industries, there is no denying the fact that some criteria are likely to be unique to the power industry. This research aims to understand what constitutes the suitable supplier selection criteria in a power utility. This study reveals some interesting findings in regard to how engineers perceive the importance of each criterion and strongly suggest that product quality, price and delivery are key determination in the supplier evaluation process. Eighteen criteria considered for this study were mapped onto their respective cluster, namely: supplier�s organizational system and technology, buyer-supplier relationship and economic value. The findings of this study should assist various groups of stakeholder (e.g. suppliers, buyers and end-users) to gain a better understanding of social behaviour in making decisions of purchase, particularly with regard to power utilities.

MAINTENANCE STRATEGY SELECTION USING AHP AND COPRAS UNDER FUZZY ENVIRONMENT / PRIEŽIŪROS STRATEGIJOS PARINKIMAS TAIKANT AHP IR COPRAS METODUS NEAPIBRĖŽTOSE SITUACIJOSE

Asset management, as a systematic process of operating, maintaining, and upgrading physical assets, is an important element of decision-making in heavy equipment management and operation. Maintenance strategy selection plays a significant role in mining design. However, the nature of maintenance strategy selection is a complex multi-criteria decision making (MCDM) problem including both tangible and intangible parameters which are often in conflicting with each other. As well as when decision makers are uncertain in determining and defining the ratings and the weights of alternatives and criteria respectively, fuzzy theory provides an appropriate tool to handle the existing uncertainties. In this paper, a new fuzzy MCDM method based on the concepts of COPRAS (COmplex PRoportional ASsessment) and AHP (Analytical Hierarchy Process) was proposed to evaluate the feasible maintenance strategy. The linguistic terms are employed to assess the ratings and weights. Fuzzy AHP is utilized to calculate the weights of the evaluation criteria; then, the rankings of alternatives are computed based on fuzzy sets theory and COPRAS. A real world case study is presented to illustrate a potential application of the proposed model. Santrauka Turto valdymas, kaip sistemingas veiklos procesas materialiajam turtui palaikyti ir atnaujinti, yra svarbus sprendimų priėmimo sandas, reikalingas sunkiajai įrangai valdyti ir naudoti. Pasirinkti priežiūros strategiją yra ypač svarbu projektuojant kasybą. Tačiau techninės priežiūros strategijos parinkimo pobūdis yra sudėtingas daugiatikslio sprendimų priėmimo (MCDM) uždavinys, apimantis tiek materialius, tiek nematerialius aspektus, tarpusavyje dažnai prieštaraujančius. Kai sprendimų priėmėjui kyla neaiškumų nustatant ir apibrėžiant rodiklių vertes ir svorius, neraiškiųjų aibių teorija yra tinkama priemonė esamam neapibrėžtumui aprašyti. Straipsnyje pateikiamas naujas neraiškusis MCDM būdas, pagrįstas COPRAS (kompleksinio proporcingo projektų įvertinimo) ir AHP (analitinio hierarchijų proceso) metodais, tikslingoms nekilnojamojo turto palaikymo strategijoms įvertinti. Rodiklių vertės ir svoriai yra apibrėžti lingvistinėmis sąvokomis. Neraiškusis AHP taikomas vertinimo rodiklių svoriams apskaičiuoti. Paskui alternatyvų rangai nustatyti taikant neraiškiųjų aibių teoriją ir COPRAS metodą. Naujai pasiūlytas modelis pritaikytas realiam uždaviniui spręsti.

A Methodology for Improving the Investment Portfolio Management Process for the Homeland Security Department using Quality Function Deployment

In this paper, we describe a methodology for improving homeland security investment decisions. The objective is to evaluate multitechnology, multiyear investment choices and the associated development and deployment risks associated with new technologies. The budgeting process in the Homeland Security Department is a complex multicriteria decision problem involving a distributed network of decision makers with diverse areas of expertise. The decision problem in Homeland Security involves game-theoretic aspects as the terrorists are likely to alter their strategies depending on the defensive counter measures selected in the budget. We propose a two-phased systems approach. The first phase employs a visualization tool based on Quality Function Deployment to develop an initial budget allocation. The second phase involves an iterative approach to project selection that dynamically adjusts the investment portfolio based on anticipated reactions taken by the terrorists. This paper is based on a study done as part of a research project for the Department of Homeland Security (DHS). We present a high-level view of the methodology and illustrate it with examples.

Combining VIKOR with GRA techniques to evaluate service quality of airports under fuzzy environment

The aim of this paper was to present an effective approach for evaluating service quality of Northeast-Asian international airports by conducting customer surveys. In general, evaluation of service quality is a complex multicriteria decision-making (MCDM) problem; therefore, a complex decision process is often involved in which multiple requirements and fuzzy conditions have to be taken into consideration simultaneously. By combining concepts of VIKOR and grey relational analysis (GRA), a new fuzzy MCDM method was proposed to deal with the evaluation of service quality problems in the international airports. This model was solved by an effective algorithm, which incorporated the decision-maker’s attitude and/or preference for customers’ assessments on weights and performance ratings of each criterion. An empirical study for evaluating service quality of seven major Northeast-Asian international airports was put forth to illustrate an application of the proposed model. The study results showed that this approach is an effective means for tackling MCDM problems involving subjective assessments of qualitative attributes in a fuzzy environment.

Multiple sourcing strategies and order allocation: an ANP‐AUGMECON meta‐model

PurposeThe strategic importance of sourcing is inherent in the positioning of the purchasing operation in a supply chain and supplier evaluation – a crucial step in sourcing – is a complex multicriteria decision making (MCDM) problem. The purpose of this paper is to provide a meta‐model for supplier evaluation and order quantity allocation, based on a MCDM method, namely the Analytic Network Process (ANP) and a multiobjective mathematical programming method (MOMP), the AUGMECON.Design/methodology/approachThe proposed approach consists of two parts. The former develops and applies the ANP method in order to evaluate the suppliers in qualitative terms. The latter implements the AUGMECON method in order to find the Pareto optimal solutions for the allocation of order quantities in a multiple sourcing environment. The integrated meta‐model is exposed through an illustrative case concerning the parapharmaceutical enterprise cluster in Greece.FindingsThe proposed meta‐model constitutes an efficient method that enables managers to actively participate in the decision making process and exploit the “qualitative value” of their suppliers, while minimizing the costs and the mean delivery times. In addition, it is proved to be suitable for the enterprise clusters, as it adapts a multiple sourcing strategy and enhances the partnership among the members.Research limitations/implicationsThe outcome of the model is highly dependent on the inputs provided by the decision maker. Moreover, the ANP method is computational intensive, but this limitation can be alleviated by appropriate software tools.Originality/valueThe proposed meta‐model is an innovative approach for decision making in the area of multiple sourcing and order allocation.

Seleção e alocação de recursos em portfólio de projetos: estudo de caso no setor químico

Escolher dentre dezenas ou centenas de alternativas, aquelas que deverão compor o portfólio de projetos de uma organização e com qual prioridade, é um problema de decisão multicritério complexo. Este trabalho teve como foco duas etapas críticas da gestão de portfólio: a seleção de projetos e a alocação de recursos. A abordagem metodológica utilizada foi a pesquisa-ação, partindo-se de uma estrutura teórico-conceitual que integra os métodos AHP (Analytic Hierarchy Process) e programação inteira em um modelo híbrido. A pesquisa de campo foi desenvolvida em uma empresa do setor químico, escolhida como unidade de análise, na qual foi implementado o modelo híbrido, de tal forma que os diferentes cenários propostos fossem comparados com o cenário real da organização estudada. Pretendeu-se avaliar a importância e utilidade desse modelo no auxílio à tomada de decisões relacionadas à seleção, priorização e alocação de recursos em projetos. Como principal resultado obtido, verificou-se que o uso do modelo contribui para o alinhamento estratégico, melhora a troca de informações entre os tomadores de decisão da empresa; possibilita a simulação de cenários estratégicos em tempo real e a verificação do impacto na carteira de projetos em execução; prioriza os projetos de forma justificável e estruturada; e permite a alocação de recursos baseada em prioridades.

A hybrid model for sourcing selection with order quantity allocation with multiple objectives under fuzzy environment

In the face of acute global competition, sourcing selection with order quantity allocation is rapidly growing as a vital issue to any organisation striving for success in business and sustainable competitive advantage. Sourcing selection is a complex multi criteria decision making problem and the complexity increases with the interdependence among the selection criteria. To model the uncertainties encountered in the integrated sourcing selection and order allocation methodology, fuzzy theory is adopted. A hybrid model with the integration of data envelopment analysis and genetic algorithm is proposed in this paper. The hybrid model is illustrated for a case study.

An integrated FANP–MOLP for supplier evaluation and order allocation

In the face of acute global competition, supplier management is rapidly emerging as a crucial issue to any companies striving for business success and sustainable development. To optimize competitive advantages, a company should incorporate “suppliers” as an essential part of its core competencies. Supplier evaluation, the first step in supplier management, is a complex multi-criteria decision-making (MCDM) problem, and its complexity is further aggravated if the highly important interdependence among the selection criteria is taken into consideration. The objective of this paper is to suggest a comprehensive decision method for identifying top suppliers by considering the effects of interdependence among the selection criteria, as well as to achieve optimal allocation of orders among the selected suppliers.

Site Selection Using Hybrid Analytical Hierarchy Processing: Evidence from Taiwanese Electronics Assembly Firms in China

ABSTRACT An upswing in labor costs and currency appreciation during the 1980s caused Asian countries and economic entities such as Hong Kong, Japan, and Taiwan to search for new manufacturing sites to obtain lower manufacturing costs. China, with its huge, rapidly growing market, was one of the main options for these Asian economic dynamos. How to find an appropriate method to evaluate an optimum place for a factory setup in China is essential to an enterprise. Analytical hierarchy processing (AHP) is a method to solve complex multicriteria decision problems. However, to make decisions based only on AHP results is not sufficiently reliable, especially when the results are too close to be precisely determined. To strengthen AHP analysis, we propose a “hybrid AHP” method. This method computes an error band (EB) of final AHP scores using its 95% Confidence Interval to estimate AHP score error and calculates EB combined with a “bootstrap” to mitigate expert pectoral bias. Based on our methods, our decision rule is “maximized AHP score and minimized EB.” To verify our methods, we took Taiwanese electronic assembly manufacturers selecting manufacturing sites in China as a case study. Our research found that Eastern China has a relatively higher consensus of preference for establishing their manufacturing sites.