Multi-Objective Capacitated Facility Location Problem with Chance Constraint and Customer Preference and Solving it with Multi-Objective Evolutionary Algorithms

Q: How can I download an article?

To download an article from SID, first log in to the site, search for the article title, and click on the 'Download Article' option.

Q: How can I download an ISI article?

To download an ISI article on SID, enter the keyword or article title in the search bar, view the relevant results, click on the desired article, and select the 'Download Article' option.

Q: How can I access the SID database?

To access the SID database, visit SID.ir, create an account, and log in to access scientific resources.

Q: Is downloading articles from SID free?

Some articles on SID are available for free, while others require payment. Details are specified on the article's page.

ZARRINPOOR N.

Scientific Information Database (SID) - Trusted Source for Research and Academic Resources

Journal Paper

Paper Information

Journal: Journal of Operational Research in its Applications Year:2019 | Volume:15 | Issue:4 (59) Page(s): 37-60

Download Full-Text

مرکز اطلاعات علمی Scientific Information Database (SID) - Trusted Source for Research and Academic Resources

Persian Verion

View:

1,126

Download:

Cites:

Information Journal Paper

Title

Multi-Objective Capacitated Facility Location Problem with Chance Constraint and Customer Preference and Solving it with Multi-Objective Evolutionary Algorithms

Author(s)

ZARRINPOOR N. | Issue Writer Certificate

Keywords

Facility LocationQ1

Capacity ConstraintQ1

Customer PreferenceQ1

Chance ConstraintQ1

Multi-Objective Harmony SearchQ1

NSGA-IIQ1

Abstract

Facility Location decisions are considered as the most important strategic decisions of organizations, and since they need large investment costs, changing in these decisions will be often impossible. Therefore, it seems necessary to decide about Facility Location with regard to the constraints and assumptions of real world in an optimal way. In this article, a Facility Location model is proposed from both the service provider’ s point of view and customer’ s perspective with the objective of minimizing the fixed cost and maximizing captured demands. The Customer Preference is considered in the model and based on it, customers choose facilities on the basis of the quality, travel time and service expense. With regard to the uncertain nature of customer’ s demand in the real world and limited capacity of facilities, Chance Constraint is taken into account to the model which ensures the customer’ s demand will be satisfied with a certain service level. Due to the NP-hard nature of the problem, a Multi-Objective Harmony Search (MOHS) algorithm and a non-dominated sorting genetic algorithm-II (NSGA-II) are proposed to solve the model. In order to calibrate the parameters of the proposed algorithms, the Taguchi method is utilized. The performance of proposed algorithms are compared in terms of different performance metrics such as error ratio, generational distance, spacing metric, diversification metric, number of Pareto-optimal solutions and computational time. Finally, the results are evaluated statistically by 2-sample t-test to determine if there is any significant difference among algorithms in any performance metric. The numerical results show that in total MOHS outperforms NSGA-II.

Cites

No record.

References

No record.

Cite

APA: Copy

ZARRINPOOR, N.. (2019). Multi-Objective Capacitated Facility Location Problem with Chance Constraint and Customer Preference and Solving it with Multi-Objective Evolutionary Algorithms. JOURNAL OF OPERATIONAL RESEARCH AND ITS APPLICATIONS (JOURNAL OF APPLIED MATHEMATICS), 15(4 (59) ), 37-60. SID. https://sid.ir/paper/164486/en

Vancouver: Copy

ZARRINPOOR N.. Multi-Objective Capacitated Facility Location Problem with Chance Constraint and Customer Preference and Solving it with Multi-Objective Evolutionary Algorithms. JOURNAL OF OPERATIONAL RESEARCH AND ITS APPLICATIONS (JOURNAL OF APPLIED MATHEMATICS)[Internet]. 2019;15(4 (59) ):37-60. Available from: https://sid.ir/paper/164486/en

IEEE: Copy

N. ZARRINPOOR, “Multi-Objective Capacitated Facility Location Problem with Chance Constraint and Customer Preference and Solving it with Multi-Objective Evolutionary Algorithms,” JOURNAL OF OPERATIONAL RESEARCH AND ITS APPLICATIONS (JOURNAL OF APPLIED MATHEMATICS), vol. 15, no. 4 (59) , pp. 37–60, 2019, [Online]. Available: https://sid.ir/paper/164486/en

Related Journal Papers