An O(n3 L)primal-dual potential reduction algorithm for solving convex quadratic programs
Mathematical Programming: Series A and B
Basic techniques for lot streaming
Operations Research
On the complexity of cooperative solution concepts
Mathematics of Operations Research
The flexibility of production processes: a general framework
Management Science
Information distortion in a supply chain: the bullwhip effect
Management Science - Special issue on frontier research in manufacturing and logistics
Capacity Allocation Using Past Sales: When to Turn-And-Earn
Management Science
A Postponement Model for Demand Management
Management Science
Supply chain scheduling: Batching and delivery
Operations Research
Managing Flexible Capacity in a Make-to-Order Environment
Management Science
Integrated Scheduling of Production and Distribution Operations
Management Science
Supply chain scheduling: sequence coordination
Discrete Applied Mathematics - Special issue: International symposium on combinatorial optimization CO'02
Order Assignment and Scheduling in a Supply Chain
Operations Research
IEEE Transactions on Mobile Computing
Scheduling: Theory, Algorithms, and Systems
Scheduling: Theory, Algorithms, and Systems
Supply Chain Scheduling: Conflict and Cooperation in Assembly Systems
Operations Research
Cost Allocation for Joint Replenishment Models
Operations Research
A Stochastic Programming Duality Approach to Inventory Centralization Games
Operations Research
Journal of Computer and System Sciences
Hi-index | 0.00 |
We consider a multiple product supply chain where a manufacturer receives orders from several distributors. If the orders cannot all be met from available production capacity, then the manufacturer allocates that capacity and a set of resubmittable orders among the distributors. The distributors may share their allocated capacity among themselves before submitting revised orders. Finally, the manufacturer schedules the revised orders to minimize its cost. We consider three practical coordination issues. First, we estimate the benefit to the manufacturer from considering scheduling costs and constraints in making capacity and order allocation decisions. Second, we estimate the additional profit that the distributors achieve when they share their allocated capacity. Third, we estimate the value of coordination between the manufacturer and the distributors. Our work is among the first to consider all three issues simultaneously. We model scheduling costs and constraints within the manufacturer's capacity allocation problem. We model the distributors' capacity sharing problem as a cooperative game that has properties that are unique within cooperative game theory. Finally, we develop optimal algorithms for all the models defined by the three coordination issues. Our exact evaluation of decisions about the appropriate coordination level improves managers' ability to make those decisions.