Integrated Competitive Pricing and Transshipment Problem for Short Life Cycle Products’ Supply Chain | Zendy

Alireza Taheri-Moghadam | Zendy; Jafar Razmi | Zendy; Fariborz Jolai | Zendy; Ata Allah Taleizadeh | Zendy

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Integrated Competitive Pricing and Transshipment Problem for Short Life Cycle Products’ Supply Chain

Author(s) -

Alireza Taheri-Moghadam,

Jafar Razmi,

Fariborz Jolai,

Ata Allah Taleizadeh

Publication year - 2019

Publication title -

international journal of engineering. transactions b: applications

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 0.213

H-Index - 17

ISSN - 1728-144X

DOI - 10.5829/ije.2019.32.08b.16

Subject(s) - transshipment (information security) , supply chain , computer science , heuristic , supply chain management , operations research , competitive advantage , supply chain network , sensitivity (control systems) , competition (biology) , product life cycle management , mathematical optimization , business , engineering , mathematics , marketing , artificial intelligence , ecology , electronic engineering , biology

This paper integrates competitive pricing and network design problems for the short life cycle products. The pricing problem determines selling prices of the products for different life cycle phases in a competitive market, as well as acquisition management of returned products. Besides, the selling and acquisition prices are related to the distance between distribution centers and customers. The network design problem aims to determine network flow and fleet assignment in each route. The proposed model is solved by various methods including exact and meta-heuristic approaches. The model and solving approaches have been validated and verified by several simulated examples and sensitivity analyses. Considering life cycle phases, competitive pricing, and transshipment problems as an integrated model, provides a new approach for the optimum solutions, which makes it more practical for application of real cases of short life cycle products. The results showed how the competition and fleet assignment influenced the optimum solution.

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