Infinite horizon production planning with periodic demand: solvable cases and a general numerical approach

In this paper, we consider a single part-type pull manufacturing system, which controls its production rates in response to periodic demand. When tracking the demand results in a product surplus, an inventory storage cost is incurred. Likewise, if an overall shortage occurs then a backlog cost is paid. In addition, production costs accrue when the system is not idle. Given an infinite planning horizon, the objective is to determine the cyclic production rates in order to minimize the total cost. With the aid of the maximum principle, extremal behavior of the system is studied and the continuous-time production planning problem is reduced to a discrete problem with a limited number of switching points at which time the production rates change. Using this result, an efficient numerical algorithm is proposed, which will yield an approximation to the optimal solution within any desired level of accuracy. In addition, we determine the analytical solution to the problem for three special cases: (i) the system capacity is not limited and the inventory storage cost factor is equal to the backlog cost factor; (ii) the production cost is negligible; and (iii) the surplus and shortages costs are negligible.

[1]  H. Keller Numerical Methods for Two-Point Boundary-Value Problems , 1993 .

[2]  Panganamala Ramana Kumar,et al.  Distributed scheduling of flexible manufacturing systems: stability and performance , 1994, IEEE Trans. Robotics Autom..

[3]  Chang Shu,et al.  Optimal PHP production of multiple part-types on a failure-prone machine with quadratic buffer costs , 2001, IEEE Trans. Autom. Control..

[4]  P. R. Kumar,et al.  Stable distributed real-time scheduling of flexible manufacturing/assembly/disassembly systems , 1988, Proceedings of the 27th IEEE Conference on Decision and Control.

[5]  Stanley B. Gershwin,et al.  An algorithm for the computer control of a flexible manufacturing system , 1983 .

[6]  R. Srikant,et al.  Failure-prone production systems with uncertain demand , 2001, IEEE Trans. Autom. Control..

[7]  J. R. Perkins,et al.  Stable, distributed, real-time scheduling of flexible manufacturing/assembly/diassembly systems , 1989 .

[8]  S. M. Roberts,et al.  Two-point boundary value problems: shooting methods , 1972 .

[9]  Konstantin Kogan,et al.  A maximum principle based combined method for scheduling in a flexible manufacturing system , 1995, Discret. Event Dyn. Syst..

[10]  Konstantin Kogan,et al.  DGAP - The Dynamic Generalized Assignment Problem , 1997, Ann. Oper. Res..

[11]  Konstantin Kogan One-machine, N-product-type, continuous-time scheduling with a common due date: a polynomially solvable case , 2001 .

[12]  Rayadurgam Srikant,et al.  Scheduling multiple part-types in an unreliable single machine manufacturing system , 1995, Proceedings of 1995 American Control Conference - ACC'95.

[13]  B. Williams,et al.  Operations management. , 2001, Optometry.

[14]  Michael C. Caramanis,et al.  One-machine n-part-type optimal setup scheduling: analytical characterization of switching surfaces , 1998, IEEE Trans. Autom. Control..

[15]  Rayadurgam Srikant,et al.  Hedging policies for failure-prone manufacturing systems: optimality of JIT and bounds on buffer levels , 1998 .

[16]  Toshihide Ibaraki,et al.  Dynamic Generalized Assignment Problems with Stochastic Demands and Multiple Agent--Task Relationships , 2005, J. Glob. Optim..