Complex Adaptive Logistics System Optimization Using Agent-Based Modelling and Simulation

This chapter examines how to control the extreme events happening when a complex adaptive logistics system is implemented in used product remanufacturing, particularly in the used products transhipment stage. The chapter starts with an introduction about the necessity of introducing the complex adaptive logistics system. Then, the related studies dealing with similar issues are discussed in the background section. Next, the focal problem of this chapter is stated in the problem statement section. A detailed description about the approach (i.e., the agent-based modelling and simulation) can be found in the proposed methodology section. Right after this, an illustrative simulation example is discussed in the experimental study section. The potential research directions regarding the main problem considered in this chapter are highlighted in the future trends section. Finally, the conclusions drawn in the last section close this chapter.

Batch Order Picking Optimization Using Ant System

This chapter concentrates on the batch order picking for remanufactured product distribution. The chapter starts with an introduction about the issue of secondary sales channels that arise in the remanufactured product redistribution phase and the delivery-oriented service strategy in remarketing. Then, the related studies in the literature are discussed in the background section. Next, the focal problem of this chapter is stated in the problem statement section. A detailed description about the approach (i.e., ant system and MAX-MIN ant system) can be found in the proposed methodology section. Right after this, an illustrative numerical example is discussed in the experimental study section. The potential research directions regarding the main problem considered in this chapter are highlighted in the future trends section. Finally, the conclusion drawn in the last section closes this chapter.

Used Products Return Pattern Analysis Using Agent-Based Modelling and Simulation

This chapter examines the used products return service quality perceived by the end users and their corresponding willingness-to-return with respect to the used products in their possession. The chapter starts with an introduction about the issue of return quantity encountered at the used product collection stage. Then, related studies dealing with returns quantity are discussed in the background section. Next, the focal problem of this chapter is stated in the problem statement section. A detailed description about the approach (i.e., agent-based modelling and simulation) can be found in the proposed methodology section. Right after this, three simulations, with each one linked to a specific used products return scenario, are conducted in the experimental study section. The potential research directions regarding the main problem considered in this chapter are highlighted in the future trends section. Finally, the conclusion drawn in the last section closes this chapter.

Introduction to Remanufacturing and Reverse Logistics

This chapter introduces the background knowledge of the main targeted problem considered in this book (i.e., remanufacturing and its associated reverse logistics). The chapter starts with an introduction about the role of remanufacturing in environment protection. Then, the related studies dealing with the remanufacturing are outlined in the background section, which is followed by a discussion about the work dedicated to the reverse logistics. Finally, the conclusion drawn in the last section closes this chapter.

Used Product Collection Optimization Using Genetic Algorithms

This chapter addresses the collected used products transportation issue (i.e., used products are first transported from a set of collection points to a sorting centre and then returned to a facility for remanufacturing). The chapter starts with an introduction about the importance of transporting these collected returns in used products remanufacturing. Then, the related studies dealing with this issue are discussed in the background section. Next, the focal problem of this chapter (by considering timing and fuel consumption constraints) is stated in the problem statement section. A detailed description about the authors’ approach (i.e., first, formulating the targeted problem as a multiple travelling salesmen problem and then employing genetic algorithms to solve it) can be found in the proposed methodology section. Right after this, an illustrative example is explained in the experimental study section. The potential research directions regarding the main problem considered in this chapter are highlighted in the future trends section. Finally, the conclusion drawn in the last section closes this chapter.

Used Product Pre-Sorting System Optimization Using Teaching-Learning-Based Optimization

In order to improve the overall output of remanufacturable end-of-life products, used products usually have to go through a pre-sorting system for identifying the sources of returns and rating them according to their characteristics (i.e., remanufacturable and non-remanufacturable). Under these circumstances, the radio frequency identification is normally used to ensure the efficiency and effectiveness of the pre-sorting process. In the last chapter, the authors focus on the multi-objective methodology to establish an evaluation model for the returned components and products; while in this chapter, the authors deal with the radio frequency identifications’ reliability in this evaluation model during the used products’ pre-sorting procedure. The chapter starts with an introduction about the issue of used product pre-sorting process and the importance of radio frequency identification tags’ reliability. Then, related studies dealing with similar problems in the literature are discussed in the background section. Next, the focal problem of this chapter is stated in the problem statement section. A detailed description about the approach (i.e., teaching-learning-based optimization algorithm) can be found in the proposed methodology section. Right after this, an illustrative example is explained in the experimental study section. The potential research directions regarding the main problem considered in this chapter are highlighted in the future trends section. Finally, the conclusion drawn in the last section closes this chapter.

Used Product Remanufacturability Evaluation Using Fuzzy Logic

This chapter focuses on the multi-objective methodology to establish an evaluation model for returned components and products. The chapter starts with an introduction about the issue of remanufacturability and the importance of the product information technology. Then, the related studies dealing with similar problems in the literature are discussed in the background section. Next, the focal problem of this chapter is stated in the problem statement section. A detailed description about the approaches (i.e., fuzzy logic and Bayesian approaches) can be found in the proposed methodology section. Right after this, an illustrative example is explained in the experimental study section. The potential research directions regarding the main problem considered in this chapter are highlighted in the future trends section. Finally, the conclusion drawn in the last section closes this chapter.

Re-Machining Parameter Optimization Using Firefly Algorithms

This chapter presents a novel approach for identification of the re-machining parameters. The chapter starts with an introduction about the significant role of re-machining at the reprocessing stage. Then, the related studies dealing with the selection of optimum machining parameters are discussed in the background section. Next, the focal problem of this chapter is stated in the problem statement section. A detailed description about the approach (i.e., firefly algorithm) can be found in the proposed methodology section. Right after this, an illustrative example is detailed in the experimental study section. The potential research directions regarding the main problem considered in this chapter are highlighted in the future trends section. Finally, the conclusion drawn in the last section closes this chapter.

Reprocessing Cell Layout Optimization Using Hybrid Ant Systems

This chapter describes the role of reprocessing cell layout design in reducing the material handling cost at the used product post-disassembly stage. The chapter begins with the discussion of material handling cost issues encountered at the reusable parts reprocessing phase. Then, related studies in the literature are discussed in the background section. Next, the focal problem of this chapter is stated in the problem statement section. A detailed description about the approach (i.e., the hybrid ant system) can be found in the proposed methodology section. Right after this, an illustrative numerical example and the corresponding comparison study are detailed in the experimental study section. The potential research directions regarding the main problem considered in this chapter are highlighted in the future trends section. Finally, the conclusion drawn in the last section closes this chapter.

Reprocessing Operations Scheduling Using Fuzzy Logic and Fuzzy MAX-MIN Ant Systems

This chapter discusses the scheduling of the reusable components’ reprocessing operations after the used products are disassembled and classified. The chapter starts with an introduction about the issue of scheduling disassembly operations and the scheduling in remanufacturing cells encountered at the used products post-disassembly stage. Then, related studies dealing with similar problems are discussed in the background section. Next, the focal problem of this chapter is stated in the problem statement section. A detailed description about the approaches (i.e., the fuzzy logic and the fuzzy MAX-MIN ant systems) can be found in the proposed methodology section. Right after this, an illustrative example is explained in the experimental study section. The potential research directions regarding the main problem considered in this chapter are highlighted in the future trends section. Finally, the conclusion drawn in the last section closes this chapter.