Authors: Alexander Hornung, Lars Monch
Addresses: Department of Informatics, Clausthal University of Technology, Julius-Albert-Str. 4, 38678 Clausthal-Zellerfeld, Germany. ' Chair of Enterprise-wide Software Systems, Department of Mathematics and Computer Science, University of Hagen, Universitaetsstrasse 1, 58097 Hagen, Germany
Abstract: In this paper, we consider heuristic approaches for the determination of delivery quantities in a Supply Chain (SC). The problem under consideration is important for the design of delivery quantity negotiations between manufacturers and suppliers. We describe a Mixed Integer Programming (MIP) formulation for the optimisation problem to be solved. We explain how we can incorporate and use the suggested decision model into a decision-support system for Supply Chain Management (SCM). Because of the computational intractable large-sized mixed integer programs, we describe an efficient Genetic Algorithm (GA) in order to get near-to-optimal solutions of the mixed integer programs. We compare the GA with a Random Search Heuristic and a Branch and Bound (B&B) algorithm to solve the mixed integer programs. The different solution procedures are assessed with respect to solution quality and computational time based on stochastically generated test instances. The GA produces high-quality solutions with an acceptable computational effort. [Received 20 December 2006; Revised 01 June 2007; Second Revision Received 06 October 2007; Accepted 06 December 2007]
Keywords: supply chain management; SCM; delivery quantities; decision support systems; DSS; genetic algorithms; GAs; optimisation.
European Journal of Industrial Engineering, 2008 Vol.2 No.4, pp.377 - 400
Published online: 22 May 2008 *Full-text access for editors Access for subscribers Purchase this article Comment on this article