New model and heuristics for safety stock placement in general acyclic supply chain networks

Authors:
Haitao Li;Dali Jiang
Affiliations:
Department of Logistics and Operations Management, College of Business Administration, University of Missouri-St. Louis, One University Blvd, St. Louis, MO 63121, USA;Institute of Modern logistics, Logistical Engineering University, Chongqing 401311, P.R.China
Venue:
Computers and Operations Research
Year:
2012

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Abstract

We model the safety stock placement problem in general acyclic supply chain networks as a project scheduling problem, for which the constraint programming (CP) techniques are both effective and efficient in finding high quality solutions. We further integrate CP with a genetic algorithm (GA), which improves the CP solution quality significantly. The performance of our hybrid CP-GA algorithm is evaluated on randomly generated test instances. CP-GA is able to find optimal solutions to small problems in fractions of a second, and near optimal solutions of about 5% optimality gap to medium size problems in several minutes on average.