Due-date setting and priority sequencing in a multiclass M/G.1 queue
Management Science
A broader view of the job-shop scheduling problem
Management Science
Single facility due date setting with multiple customer classes
Management Science
Management Science
Due date setting with supply constraints in systems using MRP
Computers and Industrial Engineering
A scenario-based stochastic programming approach for technology and capacity planning
Computers and Operations Research
Quantity and Due Date Quoting Available to Promise
Information Systems Frontiers
Scenario Reduction Algorithms in Stochastic Programming
Computational Optimization and Applications
A Multi-Stage Stochastic Integer Programming Approach for Capacity Expansion under Uncertainty
Journal of Global Optimization
Pricing and the News Vendor Problem: a Review with Extensions
Operations Research
Combined Pricing and Inventory Control Under Uncertainty
Operations Research
Note: The Newsvendor Model with Endogenous Demand
Management Science
Dynamic Pricing and the Direct-to-Customer Model in the Automotive Industry
Electronic Commerce Research
Short-term hydropower production planning by stochastic programming
Computers and Operations Research
Scenario tree modeling for multistage stochastic programs
Mathematical Programming: Series A and B
A stochastic model for forward-reverse logistics network design under risk
Computers and Industrial Engineering
A note on scenario reduction for two-stage stochastic programs
Operations Research Letters
Price and leadtime competition, and coordination for make-to-order supply chains
Computers and Industrial Engineering
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Pricing coordination and due-date management are managerial challenges in today's competitive marketplace. Segmenting orders into classes and allocating resources based on their sensitivity to time and price can increase a firm's profit and its capacity utilization. In addition, other parameters such as production policy, inventory holding and delivery system should be considered in pricing and due-date decisions. In this paper, we consider the role of flexibility in price, lead-time and delivery in the make-to-order environment, where limited production capacity under a stochastic demand function is allowed. We develop a two-stage stochastic programming model to determine the price, lead-time and production amount jointly in each period. The difficulty of continuous distributions is avoided by using a scenario-based approach for stochastic demand. Through numerical analyses, we indicate the benefits of flexibility in delivery, price and lead-time in various environments.