A genetic algorithm for the generalised assignment problem
Computers and Operations Research
A facility location allocation model for reusing carpet materials
Computers and Industrial Engineering - Special issue on o/perational issues in environmentally conscious manufacturing
Strategic network design for reverse logistics and remanufacturing using new and old product modules
Computers and Industrial Engineering
Development of RFID-based Reverse Logistics System
Expert Systems with Applications: An International Journal
A memetic algorithm for bi-objective integrated forward/reverse logistics network design
Computers and Operations Research
Review article: A review of soft computing applications in supply chain management
Applied Soft Computing
Inventory management in a two-echelon closed-loop supply chain with correlated demands and returns
Computers and Industrial Engineering
Joint shipment consolidation and inventory decisions in a two-stage distribution system
Computers and Industrial Engineering
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As cost pressures continue to mount in this era of economic slowdowns, a growing number of firms have begun to explore the possibility of managing product returns in a more cost-efficient and timely manner. However, few studies have addressed the problem of determining the number and location of initial collection points in a multiple time horizon, while determining the desirable holding time for consolidation of returned products into a large shipment. To fill the void in such a line of research, this paper proposes a mixed-integer, nonlinear programming model and a genetic algorithm that can solve the reverse logistics problem involving both spatial and temporal consolidation of returned products. The robustness of the proposed model and algorithm was tested by its application to an illustrative example dealing with products returned from online and retail sales.