Cost-based differential pricing for a make-to-order production system in a competitive segmented market

  • Ebrahim Teimoury
  • Mohammad Modarres
  • Morteza NeishabooriEmail author
Research Article


Optimal queuing system design includes deciding about some variables such as location, capacity, price, and delivery time. In order to develop an optimized system, it is essential to solve the optimization problem for all the decision variables simultaneously. In this paper, a make-to-order system is considered. In this system, some facilities are developed in different points. According to the make-to-order system definition, these facilities keep no inventory from final product. Orders are received from customers and the requested products are assembled. Due to existence of some differences among customers, they are divided into two distinct categories including express and regular customers. Each category has purchasing and upgrading demand. Upgrading demand is related to the used products that are referred to the facilities by reverse logistics for upgrade. Profit is maximized through attracting these two types of demand from different demand points. Utilizing market segmentation, different prices can be offered to each category. Difference in price is due to difference in delivery time. It means maximum guaranteed time to deliver the product. This obligation raises customer satisfaction. But lower delivery time causes increase in price and lower power in competition. Increase is price is due to designing a queue with higher capacity. In this problem, location of facilities should be selected among some potential points. There are several competitors in each potential location. Each facility is modeled as a queuing system. In these systems, decision variables are location, capacity, price, and delivery time. Finally, the optimization problem is solved by the genetic algorithm and the optimized value for each variable is gained. Facilities with these variables will have the maximum profit.


Optimization Queuing systems Differential pricing Reverse logistics Genetic algorithm 



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Copyright information

© Springer Nature Limited 2019

Authors and Affiliations

  • Ebrahim Teimoury
    • 1
  • Mohammad Modarres
    • 2
  • Morteza Neishaboori
    • 3
    Email author
  1. 1.Department of Industrial EngineeringIran University of Science & TechnologyTehranIran
  2. 2.Department of Industrial EngineeringSharif University of TechnologyTehranIran
  3. 3.Iran University of Science & TechnologyTehranIran

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