A Hybrid Approach using the Bees Algorithm and Fuzzy-AHP for Supplier Selection

Baris Yuce; Ernesto Mastrocinque

doi:10.4018/978-1-4666-9479-8.ch007

A Hybrid Approach using the Bees Algorithm and Fuzzy-AHP for Supplier Selection

Baris Yuce, Ernesto Mastrocinque

Cardiff University

Research output: Chapter in Book/Report/Conference proceeding › Chapter › peer-review

Abstract

In this chapter, a new hybrid approach combining the Fuzzy Analytic Hierarchy Process (AHP) and the Bees Algorithm is proposed in order to solve the supplier selection problem. The Fuzzy Analytic Hierarchy Process is used to determine the importance weight of each criterion and sub-criterion considered for the supplier selection, which are quality, cost, service level, supplier profile and risk. These weights are utilized in a mathematical model to determine the optimum order level of each row material from each supplier. The model considers capacity, demand, on-time delivery, quality and bill of materials. To determine the optimum order levels, the Bees Algorithm is applied to optimize this NP-hard type model under the constraints. The results showed that the Bees Algorithm performed better than Genetic Algorithm during the optimization stage.

Original language	English
Title of host publication	Handbook of Research on Advanced Computational Techniques for Simulation-Based Engineering
Editors	Pijush Samui
Place of Publication	Hersey, PA
Publisher	IGI Global
Pages	171-194
Number of pages	24
ISBN (Electronic)	9781466694804
ISBN (Print)	9781466694798, 1466694793
DOIs	https://doi.org/10.4018/978-1-4666-9479-8.ch007
Publication status	Published - 2016

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abstract = "In this chapter, a new hybrid approach combining the Fuzzy Analytic Hierarchy Process (AHP) and the Bees Algorithm is proposed in order to solve the supplier selection problem. The Fuzzy Analytic Hierarchy Process is used to determine the importance weight of each criterion and sub-criterion considered for the supplier selection, which are quality, cost, service level, supplier profile and risk. These weights are utilized in a mathematical model to determine the optimum order level of each row material from each supplier. The model considers capacity, demand, on-time delivery, quality and bill of materials. To determine the optimum order levels, the Bees Algorithm is applied to optimize this NP-hard type model under the constraints. The results showed that the Bees Algorithm performed better than Genetic Algorithm during the optimization stage.",

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AU - Mastrocinque, Ernesto

N1 - The full text is not available on the repository.

PY - 2016

Y1 - 2016

N2 - In this chapter, a new hybrid approach combining the Fuzzy Analytic Hierarchy Process (AHP) and the Bees Algorithm is proposed in order to solve the supplier selection problem. The Fuzzy Analytic Hierarchy Process is used to determine the importance weight of each criterion and sub-criterion considered for the supplier selection, which are quality, cost, service level, supplier profile and risk. These weights are utilized in a mathematical model to determine the optimum order level of each row material from each supplier. The model considers capacity, demand, on-time delivery, quality and bill of materials. To determine the optimum order levels, the Bees Algorithm is applied to optimize this NP-hard type model under the constraints. The results showed that the Bees Algorithm performed better than Genetic Algorithm during the optimization stage.

AB - In this chapter, a new hybrid approach combining the Fuzzy Analytic Hierarchy Process (AHP) and the Bees Algorithm is proposed in order to solve the supplier selection problem. The Fuzzy Analytic Hierarchy Process is used to determine the importance weight of each criterion and sub-criterion considered for the supplier selection, which are quality, cost, service level, supplier profile and risk. These weights are utilized in a mathematical model to determine the optimum order level of each row material from each supplier. The model considers capacity, demand, on-time delivery, quality and bill of materials. To determine the optimum order levels, the Bees Algorithm is applied to optimize this NP-hard type model under the constraints. The results showed that the Bees Algorithm performed better than Genetic Algorithm during the optimization stage.

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BT - Handbook of Research on Advanced Computational Techniques for Simulation-Based Engineering

A2 - Samui, Pijush

PB - IGI Global

CY - Hersey, PA

ER -

A Hybrid Approach using the Bees Algorithm and Fuzzy-AHP for Supplier Selection

Abstract

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