A hybrid mathematical programming model for optimal project portfolio selection using fuzzy inference system and analytic hierarchy process

Tavana, Madjid; Khosrojerdi, Ghasem; Mina, Hassan; Rahman, Azimah Abd

doi:10.1016/j.evalprogplan.2019.101703

Cited by 44 publications

(21 citation statements)

References 38 publications

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“…Such rules are used in this system for simulating the process of human reasoning. FIS has some advantages, such as the benefiting from human knowledge and changeable rules to indicate experts' judgment (Asklany et al, 2011;Tavana et al, 2019). In this vein, fuzzy logic modeling techniques fall within two groups, either the Mamdani (Mamdani and Assilian, 1993) or the Takagi-Sugeno-Kang (Sugeno, 1985).…”

Section: Fuzzy Inference Systemmentioning

confidence: 99%

A decision support system for demand management in healthcare supply chains considering the epidemic outbreaks: A case study of coronavirus disease 2019 (COVID-19)

Govindan

Mina

Alavi

2020

Transportation Research Part E: Logistics and Transportation Re

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516

351

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The disasters caused by epidemic outbreaks is different from other disasters due to two specific features: their long-term disruption and their increasing propagation. Not controlling such disasters brings about severe disruptions in the supply chains and communities and, thereby, irreparable losses will come into play. Coronavirus disease 2019 (COVID-19) is one of these disasters that has caused severe disruptions across the world and in many supply chains, particularly in the healthcare supply chain. Therefore, this paper, for the first time, develops a practical decision support system based on physicians' knowledge and fuzzy inference system (FIS) in order to help with the demand management in the healthcare supply chain, to reduce stress in the community, to break down the COVID-19 propagation chain, and, generally, to mitigate the epidemic outbreaks for healthcare supply chain disruptions. This approach first divides community residents into four groups based on the risk level of their immune system (namely, very sensitive, sensitive, slightly sensitive, and normal) and by two indicators of age and pre-existing diseases (such as diabetes, heart problems, or high blood pressure). Then, these individuals are classified and are required to observe the regulations of their class. Finally, the efficiency of the proposed approach was measured in the real world using the information from four users and the results showed the effectiveness and accuracy of the proposed approach.

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Section: Fuzzy Inference Systemmentioning

confidence: 99%

A decision support system for demand management in healthcare supply chains considering the epidemic outbreaks: A case study of coronavirus disease 2019 (COVID-19)

Govindan

Mina

Alavi

2020

Transportation Research Part E: Logistics and Transportation Re

Self Cite

516

351

View full text Add to dashboard Cite

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“…They are similar; the only difference is in their output. Mamdani produces fuzzy output while Sugeno produces crisp output [ 25 , 33 ]. Since the developed system output is fuzzy, we used the Mamdani model.…”

Section: Methodsmentioning

confidence: 99%

Ranking patients on the kidney transplant waiting list based on fuzzy inference system

et al. 2022

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Background Kidney transplantation is the best treatment for people with End-Stage Renal Disease (ESRD). Kidney allocation is the most important challenge in kidney transplantation process. In this study, a Fuzzy Inference System (FIS) was developed to rank the patients based on kidney allocation factors. The main objective was to develop an expert system, which would mimic the expert intuitive thinking and decision-making process in the face of the complexity of kidney allocation. Methods In the first stage, kidney allocation factors were identified. Next, Intuitionistic Fuzzy Analytic Hierarchy Process (IF-AHP) has been used to weigh them. The purpose of this stage is to develop a point scoring system for kidney allocation. Fuzzy if-then rules were extracted from the United Network for Organ Sharing (UNOS) dataset by constructing the decision tree, in the second stage. Then, a Multi-Input Single-Output (MISO) Mamdani fuzzy inference system was developed for ranking the patients on the waiting list. Results To evaluate the performance of the developed Fuzzy Inference System for Kidney Allocation (FISKA), it was compared with a point scoring system and a filtering system as two common approaches for kidney allocation. The results indicated that FISKA is more acceptable to the experts than the mentioned common methods. Conclusion Given the scarcity of donated kidneys and the importance of optimal use of existing kidneys, FISKA can be very useful for improving kidney allocation systems. Countries that decide to change or improve the kidney allocation system can simply use the proposed model. Furthermore, this model is applicable to other organs, including lung, liver, and heart.

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“…Tavana et al. (2019) also acknowledge the challenges introduced by uncertainty conditions, as well as the existence of both quantitative and qualitative criteria. In order to deal with those challenges in IT‐related project portfolio selection, they propose a hybrid mathematical programming model which integrates fuzzy methods.…”

Section: Main Clusters Identifiedmentioning

confidence: 99%

A clustering‐based review on project portfolio optimization methods

Saiz

Lostumbo

Juan

et al. 2021

Int Trans Operational Res

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Project portfolio management and optimization constitutes a critical activity for organizations in different industrial sectors and business. The scientific literature in this subject is extremely vast, which makes it difficult to understand the connections among the existing approaches and perspectives. This paper provides a clustering map of the existing work on the subject, thus identifying the main trends and approaches from different scientific communities. After analyzing each of the identified clusters, the paper provides insights and emerging trends that can be useful both for researchers and practitioners in the area.

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A hybrid mathematical programming model for optimal project portfolio selection using fuzzy inference system and analytic hierarchy process

Cited by 44 publications

References 38 publications

A decision support system for demand management in healthcare supply chains considering the epidemic outbreaks: A case study of coronavirus disease 2019 (COVID-19)

A decision support system for demand management in healthcare supply chains considering the epidemic outbreaks: A case study of coronavirus disease 2019 (COVID-19)

Ranking patients on the kidney transplant waiting list based on fuzzy inference system

A clustering‐based review on project portfolio optimization methods

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