Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/261701 
Year of Publication: 
2019
Citation: 
[Journal:] Journal of Industrial Engineering and Management (JIEM) [ISSN:] 2013-0953 [Volume:] 12 [Issue:] 3 [Publisher:] OmniaScience [Place:] Barcelona [Year:] 2019 [Pages:] 421-431
Publisher: 
OmniaScience, Barcelona
Abstract: 
Purpose: Once a set of suppliers has been determined, according to criteria of quality, price and reliability, among others, there remains the problem of assigning orders to the selected suppliers, in order to cover the needs at the lowest cost. We consider the case in which the needs of a component for a set of plants should be covered by suppliers with linear piecewise concave cost functions, a lower bound on the order size for the non-zero deliveries and a capacity constraint. The purpose is to design procedures for solving this problem. Design/methodology/approach: With the aim of providing practical tools to solve the problem of assigning orders to suppliers with linear piecewise concave costs, two mixed integer linear programs are proposed. Findings: The two MILP models are compared through an extensive computational experiment. This shows that both models, with a slight advantage for one of them, can be solved within a very short time, even when the dimensions of the instance largely exceed those that can occur in real cases. Originality/value: The paper proposes novel models that can be used to solve the problem to optimality in reasonable times and with standard optimization software.
Subjects: 
supply management
linear piecewise concave cost
mixed integer linear programming
Persistent Identifier of the first edition: 
Creative Commons License: 
cc-by-nc Logo
Document Type: 
Article

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