Dynamic supply chain network design with capacity planning and multi-period pricing

Mohammad Fattahi; Masoud Mahootchi; Kannan Govindan; Seyed Mohammad Moattar Husseini

doi:10.1016/j.tre.2015.06.007

Dynamic supply chain network design with capacity planning and multi-period pricing

Mohammad Fattahi, Masoud Mahootchi, Kannan Govindan^*, Seyed Mohammad Moattar Husseini

^*Corresponding author for this work

Research output: Contribution to journal › Article › peer-review

74 Citations (Scopus)

Abstract

This paper addresses a new problem in designing and planning a multi-echelon and multi-product supply chain network over a multi-period horizon in which customer zones have price-sensitive demands. Based on price-demand relationships, a generic method is presented to obtain price levels for products and then, a mixed-integer linear programming model is developed. Due to the problem intractability, a simulated annealing algorithm that uses some developed linear relaxation-based heuristics for capacity planning and pricing is presented. Numerical results demonstrate the significance of the model as well as the efficiency of the solution algorithm and linear relaxation-based heuristics.

Original language	English
Pages (from-to)	169-202
Number of pages	34
Journal	Transportation Research Part E: Logistics and Transportation Review
Volume	81
Early online date	24 Jul 2015
DOIs	https://doi.org/10.1016/j.tre.2015.06.007
Publication status	Published - 1 Sept 2015
Externally published	Yes

Keywords

Dynamic supply chain network design
Capacity planning
Multi-period pricing approach
Simulated annealing
Linear relaxation-based heuristics

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10.1016/j.tre.2015.06.007

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title = "Dynamic supply chain network design with capacity planning and multi-period pricing",

abstract = "This paper addresses a new problem in designing and planning a multi-echelon and multi-product supply chain network over a multi-period horizon in which customer zones have price-sensitive demands. Based on price-demand relationships, a generic method is presented to obtain price levels for products and then, a mixed-integer linear programming model is developed. Due to the problem intractability, a simulated annealing algorithm that uses some developed linear relaxation-based heuristics for capacity planning and pricing is presented. Numerical results demonstrate the significance of the model as well as the efficiency of the solution algorithm and linear relaxation-based heuristics.",

keywords = "Dynamic supply chain network design, Capacity planning, Multi-period pricing approach, Simulated annealing, Linear relaxation-based heuristics",

author = "Mohammad Fattahi and Masoud Mahootchi and Kannan Govindan and {Moattar Husseini}, {Seyed Mohammad}",

note = "Research funded by Forsknings-og Innovationsstyrelsen.",

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AU - Fattahi, Mohammad

AU - Mahootchi, Masoud

AU - Govindan, Kannan

AU - Moattar Husseini, Seyed Mohammad

N1 - Research funded by Forsknings-og Innovationsstyrelsen.

PY - 2015/9/1

Y1 - 2015/9/1

N2 - This paper addresses a new problem in designing and planning a multi-echelon and multi-product supply chain network over a multi-period horizon in which customer zones have price-sensitive demands. Based on price-demand relationships, a generic method is presented to obtain price levels for products and then, a mixed-integer linear programming model is developed. Due to the problem intractability, a simulated annealing algorithm that uses some developed linear relaxation-based heuristics for capacity planning and pricing is presented. Numerical results demonstrate the significance of the model as well as the efficiency of the solution algorithm and linear relaxation-based heuristics.

AB - This paper addresses a new problem in designing and planning a multi-echelon and multi-product supply chain network over a multi-period horizon in which customer zones have price-sensitive demands. Based on price-demand relationships, a generic method is presented to obtain price levels for products and then, a mixed-integer linear programming model is developed. Due to the problem intractability, a simulated annealing algorithm that uses some developed linear relaxation-based heuristics for capacity planning and pricing is presented. Numerical results demonstrate the significance of the model as well as the efficiency of the solution algorithm and linear relaxation-based heuristics.

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KW - Capacity planning

KW - Multi-period pricing approach

KW - Simulated annealing

KW - Linear relaxation-based heuristics

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JO - Transportation Research Part E: Logistics and Transportation Review

JF - Transportation Research Part E: Logistics and Transportation Review

ER -

Dynamic supply chain network design with capacity planning and multi-period pricing

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Keywords

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