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112 results on '"Hajipour, Vahid"'

6. A System Design Perspective for Business Growth in a Crowdsourced Data Labeling Practice.

Author

Hajipour, Vahid, Jalali, Sajjad, Santos-Arteaga, Francisco Javier, Vazifeh Noshafagh, Samira, and Di Caprio, Debora

Subjects
*SYSTEMS design, *CROWDSOURCING, *PAYMENT, *PARTICIPATION, *PROFITABILITY
Abstract

Data labeling systems are designed to facilitate the training and validation of machine learning algorithms under the umbrella of crowdsourcing practices. The current paper presents a novel approach for designing a customized data labeling system, emphasizing two key aspects: an innovative payment mechanism for users and an efficient configuration of output results. The main problem addressed is the labeling of datasets where golden items are utilized to verify user performance and assure the quality of the annotated outputs. Our proposed payment mechanism is enhanced through a modified skip-based golden-oriented function that balances user penalties and prevents spam activities. Additionally, we introduce a comprehensive reporting framework to measure aggregated results and accuracy levels, ensuring the reliability of the labeling output. Our findings indicate that the proposed solutions are pivotal in incentivizing user participation, thereby reinforcing the applicability and profitability of newly launched labeling systems. [ABSTRACT FROM AUTHOR]

Published
2024
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47. Pricing and location decisions in multi-objective facility location problem with M / M / m / k queuing systems.

Author

Tavakkoli-Moghaddam, Reza, Vazifeh-Noshafagh, Samira, Taleizadeh, Ata Allah, Hajipour, Vahid, and Mahmoudi, Amin

Subjects
PRICING, FACILITY location problems, INDUSTRIAL location, LOCATION analysis, MIXED integer linear programming, GENETIC algorithms
Abstract

This article presents a new multi-objective model for a facility location problem with congestion and pricing policies. This model considers situations in which immobile service facilities are congested by a stochastic demand followingM/M/m/kqueues. The presented model belongs to the class of mixed-integer nonlinear programming models and NP-hard problems. To solve such a hard model, a new multi-objective optimization algorithm based on a vibration theory, namely multi-objective vibration damping optimization (MOVDO), is developed. In order to tune the algorithms parameters, the Taguchi approach using a response metric is implemented. The computational results are compared with those of the non-dominated ranking genetic algorithm and non-dominated sorting genetic algorithm. The outputs demonstrate the robustness of the proposed MOVDO in large-sized problems. [ABSTRACT FROM AUTHOR]

Published
2017
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49. An extended compromise ratio method for fuzzy group multi-attribute decision making with SWOT analysis

Author

UCL - SSH/IMMAQ/CORE - Center for operations research and econometrics, Hatami-Marbini, Adel, Tavana, Madjid, Hajipour, Vahid, Kangi, Fatemeh, Kazemi, Abolfazl, UCL - SSH/IMMAQ/CORE - Center for operations research and econometrics, Hatami-Marbini, Adel, Tavana, Madjid, Hajipour, Vahid, Kangi, Fatemeh, and Kazemi, Abolfazl

Abstract

The technique for order preference by similarity to ideal solution (TOPSIS) is a well-known multi-attribute decision making (MADM) method that is used to identify the most attractive alternative solution among a finite set of alternatives based on the simultaneous minimization of the distance from an ideal solution (IS) and the maximization of the distance from the nadir solution (NS). We propose an alternative compromise ratio method (CRM) using an efficient and powerful distance measure for solving the group MADM problems. In the proposed CRM, similar to TOPSIS, the chosen alternative should be simultaneously as close as possible to the IS and as far away as possible from the NS. The conventional MADM problems require well-defined and precise data; however, the values associated with the parameters in the real-world are often imprecise, vague, uncertain or incomplete. Fuzzy sets provide a powerful tool for dealing with the ambiguous data. We capture the decision makers’ (DMs’) judgments with linguistic variables and represent their importance weights with fuzzy sets. The fuzzy group MADM (FGMADM) method proposed in this study improves the usability of the CRM. We integrate the FGMADM method into a strengths, weaknesses, opportunities and threats (SWOT) analysis framework to show the applicability of the proposed method in a solar panel manufacturing firm in Canada.

Published
2013

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