A GRASP for Supply Chain Optimization with Financial Constraints per Production Unit

Kemmoe, Sylverin; Lacomme, Philippe; Tchernev, Nikolay; Quilliot, Alain

doi:10.1007/978-1-4614-6322-1_10

Cited by 2 publications

(1 citation statement)

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“…Local search phase: We chose to use a local search relying on the neighborhood from (Van Laarhoven et al, 1992). The algorithm of the local search procedure can be found in (Kemmoe et al, 2011b).…”

Section: Specificitiesmentioning

confidence: 99%

An Optimization Approach for Job-shop with Financial Constraints - In the Context of Supply Chain Scheduling Considering Payment Delay between Members

Tchomte

Lamy

Tchernev

2015

Proceedings of the International Conference on Operations Research and Enterprise Systems

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In this paper the use of Job-Shop Scheduling Problem (JSSP) is addressed as a support for a supply chain scheduling considering financial exchange between different supply chain partners. The financial exchange is considered as the cash flow exchanges between different upstream and downstream partners. Moreover, several suppliers are involved in operations. The problem under study can be viewed as an extension of the classical JSSP. Machines are considered as business or logistic units with their own treasury and financial exchanges happen between the different partners. The goal then is to propose the best schedule considering initial cash flows in treasuries as given data. The problem is formulated as integer linear programming model, and then a powerful GRASPxELS algorithm is developed to solve large scale instances of the problem. The experiments on instances with financial constraints proved the methods addressed the problem efficiently in a short amount of time, which is less than a second in average.

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Section: Specificitiesmentioning

confidence: 99%