Back to Search

Dynamic facility location with supplier selection under quantity discount

Title	Dynamic facility location with supplier selection under quantity discount
Author	Emirhüseyinoğlu, Görkem, Ekici, Ali
Publication Date:	2019-08
Publication Place	- Elsevier
Subject	Dynamic facility location, Supplier selection, Quantity discount, Iterative algorithm
Type	Periodical
Language	English
Digital	Yes
Manuscript	No
Library:	Özyeğin University
Library Asset ID	0360-8352
Record ID	539adf18-8295-4aab-91d8-572c261d7560
Library Location	Industrial Engineering
Date	2019-08
Sample Text	Retailers have to consider several factors when making facility location decisions including suppliers' and customers' locations, customer demand and price offered by suppliers. In this study, we analyze the multi-period facility location decisions of a retailer which procures the products from multiple suppliers under an incremental quantity discount scheme and in turn satisfies an exogenous demand. The retailer decides (i) where and when to open a facility, (ii) how much to order from each supplier in each time period, and (iii) from which facility locations to satisfy the demand. We formulate the problem as a mixed-integer mathematical model. To handle large instances, we develop a decomposition-based solution approach which considers the decisions in the first echelon (suppliers and facilities) and the second echelon (facilities and customers) in an iterative manner until convergence. We propose two implementations of the proposed solution approach. The first one limits the search space by considering only a subset of the facility locations for each customer. In the second implementation of the proposed solution approach, we develop a novel two-phase strategy where we first eliminate some of the facility locations entirely from the problem using a simplified version of the first approach and then implement the first approach to the reduced set of facility locations. We demonstrate the effectiveness of the heuristic approaches through an extensive computational study. The proposed heuristics provide significantly better results compared to a simple heuristic inspired by a related study. Moreover, we observe that for small instances both heuristics provide solutions with quite low optimality gaps and for larger instances they find better solutions in less amount of time when compared against CPLEX results obtained within a 12-h time limit.
DOI	10.1016/j.cie.2019.05.023
Cilt	134

View in source Özyeğin University Özyeğin University - Historical works, archives, and periodicals search engine

Özyeğin University

Dynamic facility location with supplier selection under quantity discount

Author Emirhüseyinoğlu, Görkem, Ekici, Ali

Publication Date 2019-08

Publication Place - Elsevier

Subject Dynamic facility location, Supplier selection, Quantity discount, Iterative algorithm

Type Periodical

Language English

Digital Yes

Manuscript No

Library Özyeğin University

Library Asset ID 0360-8352

Record ID 539adf18-8295-4aab-91d8-572c261d7560

Library Location Industrial Engineering

Date 2019-08

Sample Text Retailers have to consider several factors when making facility location decisions including suppliers' and customers' locations, customer demand and price offered by suppliers. In this study, we analyze the multi-period facility location decisions of a retailer which procures the products from multiple suppliers under an incremental quantity discount scheme and in turn satisfies an exogenous demand. The retailer decides (i) where and when to open a facility, (ii) how much to order from each supplier in each time period, and (iii) from which facility locations to satisfy the demand. We formulate the problem as a mixed-integer mathematical model. To handle large instances, we develop a decomposition-based solution approach which considers the decisions in the first echelon (suppliers and facilities) and the second echelon (facilities and customers) in an iterative manner until convergence. We propose two implementations of the proposed solution approach. The first one limits the search space by considering only a subset of the facility locations for each customer. In the second implementation of the proposed solution approach, we develop a novel two-phase strategy where we first eliminate some of the facility locations entirely from the problem using a simplified version of the first approach and then implement the first approach to the reduced set of facility locations. We demonstrate the effectiveness of the heuristic approaches through an extensive computational study. The proposed heuristics provide significantly better results compared to a simple heuristic inspired by a related study. Moreover, we observe that for small instances both heuristics provide solutions with quite low optimality gaps and for larger instances they find better solutions in less amount of time when compared against CPLEX results obtained within a 12-h time limit.

DOI 10.1016/j.cie.2019.05.023

Cilt 134