Assignment of trainees to software project requirements: A stable matching based approach

Gharote, Mangesh; Patil, Rahul; Lodha, Sachin; Raman, Rajiv

doi:10.1016/j.cie.2015.05.017

Cited by 20 publications

(4 citation statements)

References 29 publications

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“…Considering the preference lists with ties in the two-sided stable matching problem, Kamiyama (2014) proposed an approach to finding a stable and Pareto efficient matching scheme with a time complexity of O(m4⁡log⁡n+m3log2n). For the two-sided market with large number of agents it is difficult and time consuming to generate the required preferences, so Gharote et al. (2015) proposed a method to predict preferences for all agents using an additive utility function, and then described a mathematical formulation with which to find a stable matching scheme.…”

Section: Literature Reviewmentioning

confidence: 99%

A systematic model of stable seller–buyer matching with true preference induction in E-commerce platform

Gao

Ye²,

Huang³

et al. 2022

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PurposeThis paper mainly focuses on how to induce all members to represent members' true preferences for supply and demand matching of E-commerce platform in order to generate stable matching schemes with more social welfare of Multi-agent Matching Platform (MMP) and individually stable advantages than traditional methods.Design/methodology/approachAn MMP is designed. Meanwhile, a true preference inducing method, Lower-Bid Ranking (LBR), is proposed to reduce the number of false preferences, which is helpful to solve the problem that too much false preferences leads to low efficiency of platform operation and supply and demand matching. Then, a systematic model of LBR-based Stable Matching (SM-LBR) is proposed.FindingsTo obtain an ideal transaction partner, the adequate preference ordering and modifying according to market environment is needed for everyone, and the platform should give full play to the platforms' information advantages and process historical transaction and cooperation data. Meanwhile, the appropriate supply and demand matching is beneficial to improve the efficiency and quality of platform operation, and the design of matching guidance mechanism is essential.Originality/valueThe numerical experiments show that, the proposed model (SM-LBR) can induce members to represent the model's true preferences for stable matching and generate effective matchings with more social welfare of MMP and individually stable advantages than traditional methods, which may provide necessary method and model reference for the research of stable matching and E-commerce platform operation.

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Section: Literature Reviewmentioning

confidence: 99%

A systematic model of stable seller–buyer matching with true preference induction in E-commerce platform

Gao

Ye²,

Huang³

et al. 2022

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show abstract

“…Furthermore, the stable matching ensures that every element a i in the set A is assigned the best element bi in set B, based on the preference. The concept of two-sided matching problems was first demonstrated for college admissions by Gale and Shapley (1962) and later extended to real-life problems, such as 'roommate assignment' problem (Irving, 1985), 'workforce assignment' problem (Gharote et al, 2015), 'student-project allocation (SPA)' problem (Abraham et al, 2007;Teo and Ho, 1998) etc.…”

Section: Existing Spa Approachesmentioning

confidence: 99%

Semantic SPA framework for situational student-project allocation in education

Rao¹

2020

IJISC

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Web 3.0 technologies have redefined the way classical problems in education are solved. The classical problems are constrained by interoperability challenges that can be addressed using semantic technologies. Student-project allocation (SPA) is one such classical problem in education, whose solution lies in finding a stable matching between student-project pairs. Although many methods exist to solve the SPA problem, recent developments in higher education, such as globalisation, has triggered interoperability challenge because of diversity in student and expert availability across disciplines, campuses, and universities. The author proposes the semantic SPA framework that addresses the interoperability challenge, by leveraging the existing semantic investments made by the educational institutions. The framework standardises the SPA data elements formally using semantic Web concepts, proposes reference ontology for the situational SPA problem, and adopts a semantic Web service approach, using OWL-S, for development. The OWL-S specification enables the automatic discovery, composition, and invocation of the Web services by educational Institutions or semantic agents on the Web, for situational SPA scenarios.

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“…The two-sided matching decision making (TSMDM) is about how to match the agents of two sides according to their own preferences. There exist a large number of TSMDM problems in reality, such as taxi dispatching and stable marriage [1,2], college admissions [3], job matchings [4], and staff designation [5]. Hence, the TSMDM is a hot theme with far-ranging actual backgrounds.…”

Section: Introductionmentioning

confidence: 99%

Hesitant fuzzy linguistic two-sided matching decision making

Yue¹,

Yu²,

Peng³

et al. 2018

Filomat

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This paper combines the theory of hesitant fuzzy linguistic term sets (HFLTSs) with two-sided matching decision making (TSMDM). The related definitions of HFLTSs and two-sided matchings (TSMs) are introduced. Then, the problem of TSMDM with HFLTSs is presented. For solving this problem, a model of TSMDM with HFLTSs is developed. The AHP method is used to determine the important degrees of agents of each side. On this base, the model of TSMDM can be changed into a double-goal model with HFLTSs. Then, the double-goal model with HFLTSs is changed into the double-goal model with scores through using the proposed score function. Furthermore, the double-goal model can be changed into a single-goal model by using the linear weighting technique once again. The scheme of TSM can be obtained through solving the single-goal model. At last, an example with sensitive analysis is provided for the illustration of the presented approach of TSM.

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Assignment of trainees to software project requirements: A stable matching based approach

Cited by 20 publications

References 29 publications

A systematic model of stable seller–buyer matching with true preference induction in E-commerce platform

A systematic model of stable seller–buyer matching with true preference induction in E-commerce platform

Semantic SPA framework for situational student-project allocation in education

Hesitant fuzzy linguistic two-sided matching decision making

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