A fuzzy MADM approach for project selection: a six sigma case study

Rathi, Rajeev; Khanduja, Dinesh; Sharma, Sanjay Kumar

doi:10.5267/j.dsl.2015.11.002

Cited by 35 publications

(23 citation statements)

References 38 publications

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“…Paul et al (2016) used the ARAS method to evaluate the police performance in different states and union territories of India in order to decrease the crime rate by taking immediate actions on the poor under performing police force of the state. Rathi et al (2016) developed a project selection approach by using fuzzy based VIKOR and TOP-SIS methodology by considering seven criteria and the weights are evaluated by using modified digital logic (MDL) method.…”

Section: Literature Reviewmentioning

confidence: 99%

Selecting the best mobile model by applying AHP-COPRAS and AHP-ARAS decision making methodology

Goswami¹,

Mitra²

2020

10.5267/j.ijdns

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The main objective of this research article is to select the best mobile model among various alternatives available on the market. For this analysis 10 alternative models from different brands are selected from different online shopping website having different specifications and ranging from low budget to medium budget in terms of price. For this selection purposes two multiple criteria decision making tools (MCDM) has been adopted i.e. Complex Proportional Assessment (COP-RAS) and Additive Ratio Assessment (ARAS). The selection process is done based on four important criteria i.e. price, internal storage, RAM and brand. The weightages of the criteria are calculated by using Analytic Hierarchy Process (AHP) and these weightages are further used in COPRAS and ARAS methods. Individual COPRAS and ARAS method is applied for the selection of the best mobile and the preference ranking order of the models are also proposed by each process. The proposed ranking order by both the methods are compared and it is found that the outcome results are more or less the same using both techniques but there is a slight change in ranking of the middle-order alternatives. Both processes give model 1 and model 4 as the best and the worst models respectively among 10 alternatives.

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Section: Literature Reviewmentioning

confidence: 99%

Selecting the best mobile model by applying AHP-COPRAS and AHP-ARAS decision making methodology

Goswami¹,

Mitra²

2020

10.5267/j.ijdns

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“…The proposed decision support strategy was useful for the project managers to take decision in the perspective environment. Rathi et al [2] developed a project selection approach based on a combination of fuzzy and Multi Attribute Decision Making (MADM) techniques in order to determine proper Six Sigma projects in automotive companies. The weights of evaluation criteria were obtained using the Modi ed Digital Logic (MDL) method and nal ranking was calculated by the primacy index obtained using fuzzy based VIKOR and Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) methodologies.…”

Section: Introductionmentioning

confidence: 99%

Integrated bi-objective project selection and scheduling using Bayesian Networks: A risk- based approach

2019

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This paper presents a novel formulation for the integrated bi-objective problem of project selection and scheduling. The rst objective was to minimize the aggregated risk by evaluating the expected value of schedule delay and the second objective was to maximize the achieved bene t. To evaluate the expected aggregated impacts of risks, an objective function based on the Bayesian Networks was proposed. In the extant mathematical models of the joint problem of project selection and scheduling, projects are selected and scheduled without considering the risk network of the projects indicating the individual and interaction e ects of risks impressing the duration of the activities. To solve the model, two solution approaches were developed, one exact and one metaheuristic approach. Goal Programming (GP) method was adopted to optimally select and schedule projects. Since the problem was NP-hard (Non-deterministic Polynomial-time), an algorithm combining GP method and Genetic Algorithm (GA) was proposed, hence named GPGA. Finally, the e ciency of the proposed algorithm was assessed not only based on small-size instances, but also by generating and testing representative datasets of larger instances. The results of the computational experiments indicated that it had acceptable performance in handling large-size and more realistic problems.

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“…Using the fuzzy multi-criteria decision making methods Rathi et al (2016) prioritized and selected the six sigma projects. They used a hybrid method of the TOPSIS and VIKOR (Opricovic & Tzeng, 2007) in a fuzzy context, investigated 7 critical criteria for selecting the projects and applied the proposed method for a case study to evaluate its efficiency.…”

Section: Introductionmentioning

confidence: 99%

A hybrid lexicographic and VIKOR approach for prioritizing construction projects by considering sustainable development criteria

Jalilibal¹,

Bozorgi-Amiri²,

Khosravi³

2018

10.5267/j.jpm

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Nowadays, one of the challenges in the organizations according to budget limitations in the companies, is how to prioritize their project portfolios in the events of their strategies. In other words, organizations are seeking to allocate resources in order to gain the maximum profit according to budget limitations. In this article, a hybrid decision making method is used to prioritize construction project portfolio by considering sustainability criteria. First, Lexicographic method is applied to weight the sustainability criteria. Then, by considering the weights derived from the Lexicographic and sustainability criteria, projects are prioritized based on VIKOR method. The proposed method of this study is applied for a case study of projects in the refinery scope.

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A fuzzy MADM approach for project selection: a six sigma case study

Cited by 35 publications

References 38 publications

Selecting the best mobile model by applying AHP-COPRAS and AHP-ARAS decision making methodology

Selecting the best mobile model by applying AHP-COPRAS and AHP-ARAS decision making methodology

Integrated bi-objective project selection and scheduling using Bayesian Networks: A risk- based approach

A hybrid lexicographic and VIKOR approach for prioritizing construction projects by considering sustainable development criteria

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