Application of dispersion algorithms to supply chain optimisation

In recent years, supply chain optimisation has attracted attention that hitherto was focussed on more local issues such as optimisation of specific plant operations, individual logistic activities of distribution/routing and inventory management. Addressing this problem is a challenge not only from an optimisation perspective but also from the stand point of addressing and modeling important trade-offs. A supply chain problem consisting of production planning and distribution scheduling in two tiers is presented in this paper. A decomposition of the overall problem into aggregate production planning and 2-echelon distribution scheduling is proposed. The two individual problems are solved by applying customised dispersion algorithms on graphs that represent their constraints and objectives in the from of connections between and weights of its vertices. Results are presented for an industrial case study making comparisons with ad-hoc methods for these individual problems.

[1]  Nilay Shah,et al.  Aggregate modelling of multipurpose plant operation , 1995 .

[2]  Randolph W. Hall,et al.  Research opportunities in logistics , 1985 .

[3]  David M. Miller,et al.  An interactive, computer-aided ship scheduling system , 1987 .

[4]  Rrk Sharma Modelling a fertiliser distribution system , 1991 .

[5]  D. Blumenfeld,et al.  Analyzing trade-offs between transportation, inventory and production costs on freight networks , 1985 .

[6]  Egon Balas,et al.  A lift-and-project cutting plane algorithm for mixed 0–1 programs , 1993, Math. Program..

[7]  John G. Klincewicz,et al.  Solving a Freight Transport Problem Using Facility Location Techniques , 1990, Oper. Res..

[8]  Yosef Sheffi Some analytical problems in logistics research , 1985 .

[9]  Randolph W. Hall,et al.  Distribution Strategies that Minimize Transportation and Inventory Costs , 1985, Oper. Res..

[10]  Julian Benjamin,et al.  An analysis of mode choice for shippers in a constrained network with applications to just-in-time inventory , 1990 .

[11]  Bruce L. Golden,et al.  FUTURE DIRECTIONS IN LOGISTICS RESEARCH , 1985 .

[12]  J Gaertner Interactive computer aided shift scheduling. , 2001, Journal of human ergology.

[13]  Ronald H. Ballou,et al.  A PERFORMANCE COMPARISON OF SEVERAL POPULAR ALGORITHMS FOR VEHICLE ROUTING AND SCHEDULING , 1988 .

[14]  Randolph W. Hall,et al.  Dependence between Shipment Size and Mode in Freight Transportation , 1985, Transp. Sci..

[15]  Egon Balas,et al.  programming: Properties of the convex hull of feasible points * , 1998 .

[16]  Claus C. Carøe,et al.  A cutting-plane approach to mixed 0-1 stochastic integer programs , 1997 .

[17]  Mark S. Daskin,et al.  Logistics: An overview of the state of the art and perspectives on future research , 1985 .

[18]  Gilbert Laporte,et al.  The vehicle routing problem: An overview of exact and approximate algorithms , 1992 .

[19]  R. Sargent,et al.  A general algorithm for short-term scheduling of batch operations—II. Computational issues , 1993 .

[20]  Horst Tempelmeier Safety stock allocation in a two-echelon distribution system , 1993 .