
## A. Ai For Rsc Network Design

To optimize the performance of the RSC, there is a need to establish an effective and efficient infrastructure via optimal network design. As a result, during the past decade, many researchers are paying more and more attention to the network design for product recovery. 

Generally RSC network design is concerned with establishing an infrastructure to manage the reverse channel which often consists of final-users, collectors, and remanufacturers. In this category, many AI approaches have been utilized (see Table II). Among various methodologies, GA is the most popular one. An example can be seen from [5] where the authors address the network design problem encountered by an electronic retailer handling consumer returns. A static model is proposed which considers deterministic supply and demand. Then GA is employed to obtain a near optimal solution for the proposed model. The computational experimentation explores the trade-offs between (i) the inventory holding and shipment consolidation costs and (ii) the location costs and customer service (measured in terms of ease of access to collection centers). 

Another recent publication in this category using AI 
approaches is [6], where the authors propose a mixed integer linear programming model to minimize the transportation and fixed opening costs in a multistage reverse logistics network. Due to the NP-hard nature of such network design problems, they apply a SA algorithm with special NS
mechanisms to find the near optimal solution. 

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B. AI for EoU & EoL Products Acquisition and Assessment The condition of the EoU & EoL products acquired by remanufacturing firms through RSC often varies widely. In order to manage this variation, a firm will normally need to collect an over-demanded quantity of used products. By acquiring more excess items, the firm can not only increase its selectivity but also lower the cost of a remanufactured product. Therefore how to obtain these cores in the first place is one of the most challenge issues within remanufacturing industry. However to the best of the authors' knowledge, there is no AI technique has been actually employed in this category. This will definitely be a future research direction. 

Meanwhile the determination of the best option for EoU 
& EoL products is also an important problem faced by companies. There are five commonly used options for EoU & EoL products: direct reuse, repair, remanufacturing, recycling, and disposal. The differences between different options can be summarized as follows: 
- The reuse of the whole product as is for its original task is often referred to as direct reuse; 
- In repair option, the damaged components of EoU 
& EoL products are always changed in order to obtain a fully-functional product; 
- While the remanufacturing is always considered as the refurbishment of EoU & EoL products up to a quality level similar to a new product; 
- In terms of recycling, recovering materials from the EoU & EoL products is always its main objective; 
- The landfill or incineration of the EoU & Eol products, which is currently causing serious environment problems, is generally called disposal. 

As a result, the development of a decision model to select between these options requires the consideration of various qualitative and quantitative factors such as environmental impact, quality, legislative factors, and cost. The authors of 
[29] focus on a selection problem of EoL product recovery options for a turbocharger case. The objective is to maximize its recovery value which includes both recovery cost and quality. To solve the problem efficiently, they develop a multi-objective EA algorithm. Other applications of AI 
techniques in this category are CBR and GA (see Table III). 

TABLE III. AI FOR EOU & EOL PRODUCTS ACQUISITION AND 

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C. *AI for EoU & EoL Products Transportation* From a logistics point of view, EoU & EoL product recovery creates a reverse flow of goods that originates at the locations of product holders, also referred to as customer zones. Once the EoU & EoL products have been consolidated at certain collection center, they will always be transported to disassembly facilities where the disassembly operations, components sorting, components inspection and assessment are normally performed. After this stage, the various components of EoU & EoL products will be delivered to their different final destinations such as remanufacturing plant and disposal sites. 