Dynamic facility location with supplier selection under quantity discount

Name: Dynamic facility location with supplier selection under quantity discount
Author: Emirhüseyinoğlu, Görkem, Ekici, Ali

İsim	Dynamic facility location with supplier selection under quantity discount
Yazar	Emirhüseyinoğlu, Görkem, Ekici, Ali
Basım Tarihi:	2019-08
Basım Yeri	- Elsevier
Konu	Dynamic facility location, Supplier selection, Quantity discount, Iterative algorithm
Tür	Süreli Yayın
Dil	İngilizce
Dijital	Evet
Yazma	Hayır
Kütüphane:	Özyeğin Üniversitesi
Demirbaş Numarası	0360-8352
Kayıt Numarası	539adf18-8295-4aab-91d8-572c261d7560
Lokasyon	Industrial Engineering
Tarih	2019-08
Örnek Metin	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

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Dynamic facility location with supplier selection under quantity discount

Yazar Emirhüseyinoğlu, Görkem, Ekici, Ali

Basım Tarihi 2019-08

Basım Yeri - Elsevier

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

Tür Süreli Yayın

Dil İngilizce

Dijital Evet

Yazma Hayır

Kütüphane Özyeğin Üniversitesi

Demirbaş Numarası 0360-8352

Kayıt Numarası 539adf18-8295-4aab-91d8-572c261d7560

Lokasyon Industrial Engineering

Tarih 2019-08

Örnek Metin 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