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Proper management of supplies and their delivery greatly affects the competitiveness of companies. This paper aims to propose an integrated decision-making approach for integrated transportation and production scheduling problem in a two-stage supply chain. The objective functions are minimizing the total delivery tardiness, production cost and the emission by suppliers and vehicles and maximizing the production quality.

First, the mathematical model of the problem is presented. Consequently, a new algorithm based on a combination of the genetic algorithm (GA) and the VIKOR method in multi-criteria decision-making, named GA-VIKOR, is introduced. To evaluate the efficiency of GA-VIKOR, it is implemented in a pharmaceutical distribution company located in Iran and the results are compared with those obtained by the previous decision-making process. The results are also compared with a similar algorithm which does not use the VIKOR method and other algorithm mentioned in the literature. Finally, the results are compared with the optimized solutions for small-sized problems.

Results indicate the high efficiency of GA-VIKOR in making decisions regarding integrated production supply chain and transportation scheduling.

This research aids the manufacturers to minimize their total delivery tardiness and production cost and at the same time maximize their production quality. These improve the customer satisfaction as a part of social and manufacturer’s power of competitiveness. Furthermore, the emission minimizing objective functions directly provides benefits to the environment and the society.

This paper investigates a new supply chain scheduling the problems and presents its mathematical formulation. Moreover, a new algorithm is introduced to solve the multi-objective problems.

The purpose of this paper is to develop a new failure mode and effect analysis (FMEA) framework for evaluation, prioritization and improvement of failure modes.

A hybrid multiple criteria decision-making method combining VIKOR, decision-making trial and evaluation laboratory (DEMATEL) and analytic hierarchy process (AHP) is used to rank the risk of the failure modes identified in FMEA. The modified VIKOR method is employed to determine the effects of failure modes on together. Then the DEMATEL technique is used to construct the influential relation map among the failure modes and causes of failures. Finally, the AHP approach based on the DEMATEL is utilized to obtain the influential weights and give the prioritization levels for the failure modes.

A case study of diesel engine’s turbocharger system is provided to illustrate the potential application and benefits of the proposed FMEA approach. Results show that the new risk priority model can be effective in helping analysts find the high risky failure modes and create suitable maintenance strategies.

The proposed FMEA can overcome the shortcomings and improve the effectiveness of the traditional FMEA. Particularly, the dependence and interactions between different failure modes and effects have been addressed by the new failure analysis method.

This paper presents a systemic analytical model for FMEA. It is able to capture the complex interrelationships among various failure modes and effects and provide guidance to analysts by setting the suitable maintenance strategies to improve the safety and reliability of complex systems.

An appropriate system for analysing performance of supply chains is an important requirement for the effective utilization of the supply chains. The purpose of this paper is to develop a conceptual model for the task of analysing the performance of members of supply chains.

A thorough literature review of the methodologies proposed earlier by various authors has been made. In this paper a multi criteria decision-making (MCDM) framework comprising of two MCDM approaches is proposed for analysing performance of supply chain members.

Performance analysis of members of supply chain and the process of decision making based on the outcome of the analysis is a MCDM process. Since human judgements are often vague, the application of fuzzy concepts is appropriate for analysing the performance of supply chains. The framework proposed in this paper was validated in a company manufacturing textiles.

The methodologies proposed are of great use for large- and medium-sized enterprises. However, small organizations may not be able to allot enough resources to implement the methodologies proposed.

The framework developed can be applied for undertaking a comparative analysis of performance of members of supply chains. It can also be applied for the process of incorporation of new members into the supply chain.

Very few methods are available for analysing the performance of supply chains and the subject remains an under researched one. The major contribution of this paper is that it proposes a new framework.

A multi‐criteria model is developed for analyzing the land‐use strategies for reducing the future social and economic costs in an area with potential natural hazard. A multi‐criteria decision‐making procedure consists of generating alternatives, establishing criteria, assessment of criteria weights and application of the compromise ranking method (VIKOR). The alternatives are the scenarios of sustainable hazard effects mitigation, generated in the form of comprehensive land‐use plans. The alternative plans should consider the redevelopment of urban areas and infrastructures, multi‐purpose land use, including restrictions on building in hazardous areas. The evaluation of alternatives is implicated with imprecision (or uncertainty) of established criteria, and the fuzzy multi‐criteria model is developed to deal with “qualitative” (unquantifiable or linguistic) or incomplete information. The planning goal is to compromise competitive land uses through choice of the best (compromise) combination of uses. An application of this model is illustrated with the post‐earthquake regional planning problem in central Taiwan.

This paper aims to propose a bed and breakfast (B&B) recommendation method that takes into account review timeliness and user preferences to help consumers choose the most satisfactory B&B.

This paper proposes a B&B ranking method based on improved intuitionistic fuzzy sets. First, text mining and cluster analysis are combined to identify the concerns of consumers and construct an attribute set. Second, an attribute-level-based text sentiment analysis is established. The authors propose an improved intuitionistic fuzzy set, which is more in line with the actual situation of sentiment analysis of online reviews. Next, subjective-objective combinatorial assignments are applied, considering the consumers’ preferences. Finally, the vlsekriterijumska optimizacija i kompromisno resenje (VIKOR) algorithm, based on the improved score function, is advised to evaluate B&Bs.

A case study is presented to illustrate the use of the proposed method. Comparative analysis with other multi-attribute decision-making (MADM) methods proves the effectiveness and superiority of the VIKOR algorithm based on the improved intuitionistic fuzzy sets proposed in this paper.

Proposing a B&B recommendation method that takes into account review timeliness and user customization is the innovation of this paper. In this approach, the authors propose improved intuitionistic fuzzy sets. Compared with the traditional intuitionistic fuzzy set, the improved intuitionistic fuzzy set increases the abstention membership, which is more in line with the actual situation of attribute-level sentiment analysis of online reviews.

This paper aims to deal with the problems such as epistemic uncertainty, common cause failure (CCF) and dynamic fault behaviours that arise in complex systems and develop an effective fault diagnosis method to rapidly locate the fault when these systems fail.

First, a dynamic fault tree model is established to capture the dynamic failure behaviours and linguistic term sets are used to obtain the failure rate of components in complex systems to deal with the epistemic uncertainty. Second, a β factor model is used to construct a dynamic evidence network model to handle CCF and some parameters obtained by reliability analysis are used to build the fault diagnosis decision table. Finally, an improved Vlsekriterijumska Optimizacija I Kompromisno Resenje algorithm is developed to obtain the optimal diagnosis sequence, which can locate the fault quickly, reduce the maintenance cost and improve the diagnosis efficiency.

In this paper, a new optimal fault diagnosis strategy of complex systems considering CCF under epistemic uncertainty is presented based on reliability analysis. Dynamic evidence network is easy to carry out the quantitative analysis of dynamic fault tree. The proposed diagnosis algorithm can determine the optimal fault diagnosis sequence of complex systems and prove that CCF should not be ignored in fault diagnosis.

The proposed method combines the reliability theory with multiple attribute decision-making methods to improve the diagnosis efficiency.

The purpose of this paper is to report a study on the application of interpretative structural modelling (ISM) integrated with multi-criteria decision-making (MCDM) techniques for enabling the sustainability supplier selection.

In this paper, two approaches of hybrid MCDM methods are followed and the selection of sustainable supplier was based on the comparative results obtained from both the methods. The first hybrid approach is ISM – analytic network process (ANP) – ELimination and Et Choice Translating REality (ELECTRE II) and the second hybrid approach is ISM – ANP – Vlse Kriterijumska Optimizacija Kompromisno Resenje (VIKOR). ISM was used to identify the inter relationship between the criteria. Inter-relationship of criteria obtained from ISM will serve as an input for ANP. The weights obtained from ANP will be used in ELECTRE II and VIKOR. ELECTRE II is an outranking method, whereas VIKOR is a compromise ranking method; comparison of both the methods was carried out in this study.

In this study, two modules ISM–ANP – ELECTRE and ISM–ANP – VIKOR were compared for the problem of sustainable supplier selection. ELECTRE results with a single solution showed that Supplier 2 can be selected as the best supplier; VIKOR result shows that Supplier 1 and Supplier 2 can be selected as the best suppliers.

The selection of sustainable supplier considering the interrelationship of criteria using ISM and ranking the alternatives using compromise and outranking techniques was found to be original and novel contribution of the author.

This research proposes weighted grey relational analysis (WGRA) method to evaluate the performance of 325 multilevel dispatching rules in the wafer fabrication process.

The research methodology involves multilevel dispatching rule generation, simulations, WGRA and result analysis. A complete permutation of multilevel dispatching rules, including the partial orders, is generated from five basic rules. Performance measures include cycle time, move, tool idling and queue time. The simulation model and data are obtained from a wafer fab in Malaysia. Two seasons varying in customer orders and objective weights are defined. Finally, to benchmark performance and investigate the effect of varying values of coefficient, the models are compared against TOPSIS and VIKOR.

Results show that the seasons prefer different multilevel dispatching rules. In Normal season, the ideal first basic dispatching rule is critical ratio (CR) and CR followed by shortest processing time (SPT) is the best precedence pairing. In Peak season, the superiority of the rule no longer heavily relies on the first basic rule but rather depends on the combination of tiebreaker rules and on-time delivery (OTD) followed by CR is considered the best precedence pairing. Compared to VIKOR and TOPSIS, WGRA generates more stable rankings in this study. The performance of multicriteria decision-making (MCDM) methods is influenced by the data variability, as a higher variability produces a much consistent ranking.

As research implications, the application illustrates the effectiveness and practicality of the WGRA model in analyzing multilevel dispatching rules, considering the complexity of the semiconductor wafer fabrication system. The methodology is useful for researchers wishing to integrate MCDM model into multilevel dispatching rules. The limitation of the research is that the results were obtained from a simulation model. Also, the rules, criteria and weights assigned in WGRA were decided by the management. Lastly, the distinguishing coefficient is fixed at 0.5 and the effect to the ranking requires further study.

The research is the first deployment WGRA in ranking multilevel dispatching rules. Multilevel dispatching rules are rarely studied in scheduling research although studies show that the tiebreakers affect the performances of the dispatching rules. The scheduling reflects the characteristics of wafer fabrication and general job shop, such as threshold and look-ahead policies.

The purpose of this study is to measure the R&D performance of 81 cities in Turkey by using a scientific approach.

A four-step solution approach is developed for this problem. In the first step, a hierarchical structure of 14 indicators (including number of patents, publications, R&D expense, etc.) in three dimensions is constructed. In the second step, explicitly and implicitly spatial indicators such as university location and R&D manpower are mapped by using geographic information system (GIS). In the third step, a hybrid multi-criteria decision making model, namely, DANP that combines decision-making trial and evaluation laboratory (DEMATEL) and analytic hierarchy process (ANP) techniques is applied to assign different level of importance to the indicators. In the last step, Višekriterijumska Optimizacijai kompromisno Rešenje (VIKOR) method is used to rank the performance of 81 cities. Obtained results are visualized using GIS to show the pros and cons of each city in terms of R&D performance.

Results of the paper show that Istanbul, Ankara and Konya are ordered as contenders of best R&D performances and on the contrary, Igdir, Sirnak and Tunceli are ordered as the worst R&D performances among 81 cities.

One limitation of the study can be the considered criteria. However, all the criteria are obtained from literature and experts; thus, the paper covers as much criteria as possible.

The proposed study may allow Ministry of Science, Industry and Technology of Turkey to formulate more effective strategies to improve cities’ R&D performance. In addition, any country can apply the same methodology for measuring the R&D performance of their cities by using their related data. As the worst R&D city performances belong to the eastern part of Turkey, it can be deducted that the socio-cultural structure of the eastern part of the country needs improvement.

To the best of the author’s knowledge, this is the first study which applies a GIS-based MCDM approach for R&D performance measurement. Thus, the value of this paper belongs to both literature and real life.

Today, customers are generally perceived to be demanding higher quality and better performing products, in shorter and more predictable development cycle-times and at a lower cost. These market pressures drive firms to collaborate with possible partners in product development (PD) processes. However, the selection of a suitable partner for an effective PD is not an easy decision and is associated with complexity. The purpose of this paper is to propose an integrated multi-criteria decision-making (MCDM) approach to effectively evaluate PD partners.

The proposed evaluation procedure consists of several steps. First, based on a literature review and expert validation, the strategic main and sub-criteria of the PD partner selection process that companies consider the most important are identified. After constructing the evaluation criteria hierarchy, the criteria weights are calculated by applying the Analytic Hierarchy Process (AHP) method. The VIKOR (a compromise ranking) method is used to obtain the final partner ranking results. A case study is given to demonstrate the potential of the methodology. In the last part of the study, a sensitivity analysis is performed to determine the influence of criteria weights on the decision making process.

The PD partner evaluation model contains three main criteria, namely, partner, collaboration and PD-oriented criteria, with 13 sub-criteria. The market position, competency of the partner, compatibility, technical expertise and complementarity are found as the most considerable evaluation criteria for the ABC case company. Results of the sensitivity analysis from different cases demonstrate that the integrated AHP-VIKOR model is quite sensitive to the weights assigned to the evaluation criteria. This finding underlines the importance of forming a capable, qualified group of experts for the decision-making procedure. The results of the empirical study show that the proposed evaluation framework is practical for solving partner selection problems.

Partner selection is critical to the success of a collaborative PD process. The main contribution of this paper is the definition and development of an effective evaluation framework to guide managers for suitable PD partner selection. In our knowledge, there exists no study in the literature that combines the established AHP VIKOR model for PD partner selection problem. This study can be useful to researchers to better understand PD partner selection problem theoretically, as well as to organizations in designing better satisfying PD partner evaluation systems.