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The purpose of this paper is to determine the suitability of adopting hybridized multicriteria decision-making models as a decision tool in engineering design. This decision tool will assist design engineers and manufacturers to determine a robust design concept before simulation and manufacturing while all the design features and sub features would have been identified during the decision-making process.

Fuzzy analytical hierarchy process (FAHP) and fuzzy technique for order preference by similarity to ideal solution (FTOPSIS) are hybridized and applied to obtain optimal design of a reconfigurable assembly fixture (RAF) from a set of alternative design concepts. Design features and sub features associated with the RAF are identified and compared using fuzzified pairwise comparison matrices to obtain weights of their relative importance in the optimal design. The FAHP obtained the fuzzy synthetic extent (FSE) values of the design features and sub features. The FSE values are used as weights of the design features and sub features in generating the decision matrix. FTOPSIS and FTOPSIS based on left and right scores were adopted to predict effects of the weights. Results were obtained for normalized and unnormalized weights of the design features and its effects on the relative closeness coefficients of the design alternatives.

The improved performance of the FTOPSIS based on left and right scores is due to the involvement of the left and right scores of weights of the design features in the computation of distances from positive and negative ideal solutions. Embedding the weights of the design features in the normalized decision matrix before estimating the distances of the design concepts from ideal solutions reduces the dependency of the closeness coefficients on the weights of the design features. This also decreases the difference in the final values of the design concepts. In essence, the weights of the design features have an impact in the closeness coefficient. There is reduction in the closeness coefficients of the design concepts due to normalization of the weights of the design features. However, normalizing the weights of the design features did not affect the variations in the final values of the design concept. As the final value of the design concepts can be influenced by the normalized weights of the design features, it can be implied that normalization of weights of the sub features will also affect the decision matrix. The study has been able to proof that hybridizing FAHP and FTOPSIS can produce effective results for decisions on optimal design by the application of FTOPSIS based on left and right scores rather than the general FTOPSIS.

This research develops a hybridized multicriteria decision-making model for decision-making in engineering design. It presents a detailed extension of hybridized FAHP and FTOPSIS based on left and right scores as a useful tool for considering the relative importance of design features and sub features in optimal design selection.

Due to the increasing size and complexity of construction projects, construction engineering and management involves the coordination of many complex and dynamic processes and relies on the analysis of uncertain, imprecise and incomplete information, including subjective and linguistically expressed information. Various modelling and computing techniques have been used by construction researchers and applied to practical construction problems in order to overcome these challenges, including fuzzy hybrid techniques. Fuzzy hybrid techniques combine the human-like reasoning capabilities of fuzzy logic with the capabilities of other techniques, such as optimization, machine learning, multi-criteria decision-making (MCDM) and simulation, to capitalise on their strengths and overcome their limitations. Based on a review of construction literature, this chapter identifies the most common types of fuzzy hybrid techniques applied to construction problems and reviews selected papers in each category of fuzzy hybrid technique to illustrate their capabilities for addressing construction challenges. Finally, this chapter discusses areas for future development of fuzzy hybrid techniques that will increase their capabilities for solving construction-related problems. The contributions of this chapter are threefold: (1) the limitations of some standard techniques for solving construction problems are discussed, as are the ways that fuzzy methods have been hybridized with these techniques in order to address their limitations; (2) a review of existing applications of fuzzy hybrid techniques in construction is provided in order to illustrate the capabilities of these techniques for solving a variety of construction problems and (3) potential improvements in each category of fuzzy hybrid technique in construction are provided, as areas for future research.

The purpose of this paper is to state a hierarchy methodology to select the most promising innovative projects, based on the processes defined by the successful Project Management Institute.

Open innovation is a new option for companies to acquire knowledge; however, in a changing and global market, it is necessary to define and select properly the proposals to be financially supported. A proven multicriteria decision methodology (MCDM) is recommended in this case to hierarchize alternatives. Moreover, analytical hierarchy process (AHP) has been considered in this study as a proven and simple MCDM.

AHP has been demonstrated as a suitable option to evaluate innovative project proposals, thanks to its integration with the Project Management Institute methodology. A process example has been included to demonstrate its application.

Innovative projects and project proposal selection have always implied subjective criteria. Moreover, some of the processes defined in the methodology were not well defined in the project proposal.

The management of a project portfolio in a rational way would help decision makers to fund the most promising projects/alternatives under consideration. In this way, the inherent risk of R&D projects would be minimized.

The management of a portfolio of innovative proposals is less often addressed in the literature. This paper focuses on the hybridization of the criteria and processes described in the PMBOK Guide and an MCDM.

Various approaches have emerged to assist practitioners in making more informed decisions in highway construction projects. However, industry practitioners are still using subjective ways to make decisions. Also, researchers have developed tools and techniques with similar objectives. Lack of information on what has been developed might lead to those issues. Therefore, this paper aims to review trends of evolution, pinpoint strengths and gaps in the literature and identifies potential future directions for decision-making research in highway construction projects.

A systematic review was conducted on published articles on decision-making in highway construction projects using the Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) technique.

The analysis of 101 articles revealed that existing decision-making research in highway construction projects targets improvements in four areas: feasibility, conceptual, detailed scope and detailed design. The four areas consist of sixteen subthemes that are detailed in this study. In addition, most research involved developing decision support tools and systems as well as decision-making models, techniques and frameworks. Lastly, several research areas have emerged, such as adding more decision criteria including those with uncertainties, expanding existing decision-making models into decision support systems, benchmarking decision criteria between different sample populations and exploring inter-and intra-relationships between decision criteria.

This paper provides an overview of existing research on decision-making in highway construction projects. Also, it reveals research gaps in the body of knowledge to point out directions for future research. Finally, industry practitioners can use the findings to develop strategies for effective decision-making processes.

Reverse logistics (RL) is a type of supply chain management that moves goods from the end customer to the original manufacturer for reuse, remanufacturing and disposal purposes. Owing to growing environmental legislations and the development of new technologies in marketing, RL has attracted more significance among experts and academicians. Outsourcing RL practices to third-party reverse logistics provider (3PRLP) has been identified as one of the most important management strategies due to complexity of RL operations and the lack of available resource. Current sustainability trends have made 3PRLP assessment and selection process more complex. In order to select the 3PRLP, the existence of several aspects of sustainability motivates the experts to establish a new multi-criteria decision analysis (MCDA) approach.

With the growing complexity and high uncertainty of decision environments, the preference values of 3PRLPs are not always expressed with real numbers. As the generalized version of fuzzy set, intuitionistic fuzzy set and Fermatean fuzzy set, the theory of q-rung orthopair fuzzy set (q-ROFS) is used to permit decision experts (DEs) to their assessments in a larger space and to better cope with uncertain information. Given that the combined compromise solution (CoCoSo) is an innovative MCDA approach with higher degree of stability and reliability than several existing methods.

To exhibit the potentiality and applicability of the presented framework, a case study of S3PRLPs assessment is taken from q-rung orthopair fuzzy perspective. The assessment process consists of three sustainability aspects namely economic, environment and social dimensions related with a total of 14 criteria. Further, sensitivity and comparative analyses are made to display the solidity and strength of the presented approach. The results of this study approve that the presented methodology is more stable and efficient in comparison with other methods.

Thus, the objective of the study is to develop a hybrid decision-making methodology by combining CoCoSo method and discrimination measure with q-ROFS for selecting an appropriate sustainable 3PRLP (S3PRLP) candidate under uncertain environment. In the proposed method, a novel procedure is proposed to obtain the weights of DEs within q-ROFS context. To calculate the criteria weights, a new formula is presented based on discrimination measure, which provides more realistic weights. In this respect, a new discrimination measure is proposed for q-ROFSs.

The proposed hybridized framework provides a new performance optimization-based paradigm for analysing the failure behaviour of paneer unit (PU) in the dairy industry.

A novel fuzzy Jaya-based Lambda–Tau Optimization (JBLTO) approach-based mathematical modelling was developed for calculating various reliability indices of the considered unit. Failure mode and effect analysis (FMEA) was carried using qualitative information gathered from system's expert opinions. Fuzzy-complex proportional assessment (FCOPRAS) approach was integrated within FMEA to recognize the most critical failure causes associated with various subsystem/components.

The availability of the unit falls by 0.053% as the uncertainty level increases from ±15 to ±25% and further decreases to 0.323% as the uncertainty level increases from ±25 to ±60%. Failure causes, namely wearing in gears of gearbox (MST4), an impeller's cavitation and/or corrosion (CFP4), winding failure of electric motor (WS9), were recognized as the most critical failure causes with FCOPRAS final performance scores of 100, 100 and 100 and fuzzy combinative distance-based assessment (FCODAS) resultant assessment score of 0.5997, 1.1898 and 1.6135.

JBLTO approach-based reliability results were compared with traditional particle swarm optimization-based Lambda–Tau (PSOBLT) and traditional fuzzy Lambda–Tau (FLT) approaches for confirming the downward trend in the system's availability. The ranking results of qualitative analysis are compared with the implementation of FCODAS technique. Sensitivity analysis was executed to evaluate the robustness of the proposed hybridized framework.

The purpose of this paper is to present a decision support system (DSS) for a Colombian public utility company in order to aid decision-making at the operational level regarding route planning and travel time. The aim is to provide a tool to assist technicians that perform interruption and reconnection of domiciliary services for about 2,000 customers a day.

The real-life problem is modeled as a Single Depot Vehicle Routing Problem with Time Windows (SDVRP-TW), which is a well-known optimization problem in Operations Research/Management Science. A two-stage approach integrated into decision-making software is provided. The first stage considers the clustering of customers generated by a combination of the sweep and the k-means algorithms, while the second phase plans the routing of technicians using the nearest-neighbor and the Or-opt heuristics. The proposed approach is tested using real data sets.

In comparison with the current route planning approach, the proposed method is able to obtain savings in total travel times, improving operational productivity by 22.2 percent.

Since the analysis is carried out based on mathematical modeling, assumptions about the relationships between variables and elements of the actual complex problem might be simplified. Although the proposed approach aids the route planning, decision makers make the final decisions.

The proposed DSS has a critical impact on actual operational practices at the company. Productivity and service level are improved, while reducing operational costs. The decision-making process itself will be improved so technicians and higher decision makers can focus on performing other tasks.

The real-life problem is modeled using mathematical programming and efficiently solved through a two-stage approach based on simple, quite intuitive, solution procedures that have not been implemented for such services. In addition, as actual data from the company is employed for experimental purposes, the solution approach is tested and its efficiency and efficacy are both validated in a realistic setting, hence providing realistic behavior for decision makers at the company.

presentar un sistema de soporte a las decisiones (Decision Support System, DSS) para una empresa colombiana de servicios públicos con el fin de apoyar el proceso de toma de decisiones a nivel operativo en lo relacionado con la planeación de rutas y el tiempo de servicio. El objetivo es suministrar una herramienta que ayude a los técnicos a desempeñar el servicio de corte y reconección de servicios domiciliarios para aproximadamente 2000 clientes por día.

el problema de una empresa real es modelado como un problema de enrutamiento de vehículos un único depósito y ventanas de tiempo (Single Depot Vehicle Routing Problem with Time Windows, SDVRP-TW). Éste es un problema de optimización muy conocido en Investigación de Operaciones / Ciencias de la Administración. Se presenta un enfoque de dos etapas integrado en un software de ayuda a la toma de decisiones. La primera etapa considera el agrupamiento de los clientes generado por una combinación de los algoritmos del barrido y el k-media, mientras que la segunda fase define el plan de rutas para los técnicos utilizando las heurísticas de vecino más cercano y Or-opt. El enfoque propuesto es validado empleando datos reales.

en comparación con el plan de rutas actualmente utilizado por la empresa, el método propuesto es capaz de obtener ahorros en el tiempo total de viaje incrementando la eficiencia operativa en un 22.2%.

puesto que el análisis se lleva a cabo a partir de un modelo matemático, los supuestos sobre las relaciones entre las variables y los elementos del sistema real complejo podrían simplificarse. Además, aunque el sistema propuesto realiza la planeación de rutas, la decisión final es tomada finalmente por las personas.

el DSS propuesto tiene un impacto crítico en la práctica operativa real de la empresa. La productividad y el nivel de servicio se mejoran, mientras se reducen los costos operativos. El proceso de toma de decisiones en sí mismo se verá mejorado pues los técnicos y los tomadores de decisiones pueden enfocarse en realizar otras tareas.

el problema real es modelado utilizando programación matemática y se resuelve de forma efectiva con un procedimiento de dos etapas sencillo y básicamente intuitivo que no ha sido puesto en marcha antes para tales empresas de servicios. Además, puesto que datos reales de la empresa son utilizados en la experimentación, el enfoque de solución es validado y su eficiencia y eficacia son comprobadas en un ambiente real, suministrando así un comportamiento real para los tomadores de decisiones en la empresa.

The construction industry is a key driver of economic growth. However, the adverse impacts of construction and demolition waste (CDW) resulted from the active construction projects on the economy, environment, public health and social life necessitates an appropriate control and management of this waste stream. Developing and promoting the construction and demolition waste management (CDWM) hierarchy program at the strategic level is essential.

This study aims to propose a hybrid decision model that hybridizes the Integrated Determination of Objective Criteria Weights (IDOCRIW) and weighted aggregated sum product assessment (WASPAS) under a fuzzy environment.

The proposed method ranks the potential strategic alternatives by the sustainable development criteria to improve the performance of CDWM. As indicated in the results, the fuzzy approach in the decision-making process enables the transformation of linguistic variables into fuzzy numbers that show uncertainty and ambiguity in real-world systems. Moreover, the close correlation between the final ranking of the proposed methodology and the average priority order of the strategic alternatives obtained by five different multi-criteria decision-making (MCDM) methods implies the validity of the model performance.

This proposed model is an appropriate tool to effectively decide on the development of CDWM from a strategic point of view. It aims to establish an MCDM framework for the evaluation of effective strategies for CDWM according to the indices of sustainable development. Implementing proper operational plans and conducting research in CDWM has the highest priority, and enacting new and more stringent laws, rules and regulations against the production of CDW has secondary priority. This study contributes to the field by optimizing the CDWM by applying the top-priority strategies resulted from the proposed fuzzy hybrid MCDM methodology by the decision-makers or policy-makers to reach the best managerial strategic plan.

In the proposed methodology, the IDOCRIW technique is utilized and updated with the triangular fuzzy numbers for the first time in the literature to derive the weights of sustainable development criteria. The fuzzy WASPAS method is utilized for evaluation and providing a final ranking of the strategic alternatives.

The purpose of this paper is to introduce a model of decision-making problem in multi-criteria optimization domain for project selection. The model is built by combining the soft set theory and analytic hierarchical model under fuzziness. Soft set model gives us the opportunity to use parameterization properties. Here, the authors have proved that multiple alternatives can be reduced to make the selection process computationally efficient. Here, the authors illustrate the hybrid method by means of an application of the new mathematical model of soft set theory.

This paper is designed to excel a decision support system with multiple criteria analysis tool, analytic hierarchy process combined with soft set theory under fuzziness.

In this paper, the authors have taken four projects P1, P2, P3 and P4. As per chosen parameters of softest theory the result of the illustrative example reveals that P2 is the best project. The ranking the authors get is in the order of P2, P3, P4 and P1. The algorithm leads the authors to maximize the proper choice in the environment of imprecise information. The main advantage of this method compare to others is that this hybrid method is very simple in terms of calculation and the computational complexity of the proposed algorithm is low.

This proposed decision support strategy for an intended project manager helped to take decision in the perspective environment.

Expert evaluation is the backbone of the multi-criteria decision-making (MCDM) techniques. The experts make pairwise comparisons between criteria or alternatives in this evaluation. The mainstream research focus on the ambiguity in this process and use fuzzy logic. On the other hand, cognitive biases are the other but scarcely studied challenges to make accurate decisions. The purpose of this paper is to propose pilot filters – as a debiasing strategy – embedded in the MCDM techniques to reduce the effects of framing effect, loss aversion and status quo-type cognitive biases. The applicability of the proposed methodology is shown with analytic hierarchy process-based Technique for Order-Preference by Similarity to Ideal Solution method through a sustainable supplier selection problem.

The first filter's aim is to reduce framing bias with restructuring the questions. To manipulate the weights of criteria according to the degree of expected status quo and loss aversion biases is the second filter's aim. The second filter is implemented to a sustainable supplier selection problem.

The comparison of the results of biased and debiased ranking indicates that the best and worst suppliers did not change, but the ranking of suppliers changed. As a result, it is shown that, to obtain more accurate results, employing debiasing strategies is beneficial.

To the best of the author's knowledge, this approach is a novel way to cope with the cognitive biases. Applying this methodology easily to other MCDM techniques will help the decision makers to take more accurate decisions.