Designing dynamic reverse logistics network for post-sale service

Area of Science:

• Operations Research
• Supply Chain Management
• Industrial Engineering

Background:

• Designing integrated production-distribution networks with reverse logistics capabilities is complex.
• Post-sale services, including repairs and remanufacturing, are crucial for customer satisfaction and sustainability.
• Managing warranty returns efficiently requires strategic network design.

Purpose of the Study:

• To develop an optimization model for a multi-country production-distribution network incorporating repair and remanufacturing services.
• To minimize the overall configuration and operation costs of the network for handling returned products.
• To identify optimal facility locations, product flow for refurbishment/remanufacturing, and capacity expansion strategies.

Main Methods:

• Formulation of a mixed-integer nonlinear program (MINLP) for network design.
• Transformation of the MINLP to a mixed-integer linear program (MILP) to improve solution efficiency.
• Utilizing a randomly generated dataset to validate the model's applicability.

Main Results:

• The model determines optimal locations for new and existing facilities.
• It provides optimal distribution strategies for returned products to repair or remanufacturing centers.
• The study identifies optimal capacity expansions for plants and warehouses to support reverse logistics operations.

Conclusions:

• The developed MINLP-to-MILP model effectively optimizes the design and operation of production-distribution networks with integrated post-sale services.
• The model offers significant cost-saving potential through efficient handling of warranty returns and utilization of hybrid facilities.
• The findings provide valuable insights for firms seeking to enhance their reverse logistics and service operations.