Solving Instances of an Order Picking Model for the Second-Hand Toy Industry Combining Amalgam Case-Based Reasoning and PSO Algorithms

Abstract

An increasingly large community—mainly from emerging economies—collects and buys “click toys” (i.e., scalable and adjustable toys composed by many pieces); this type of toy has been used for educational purposes; low-cost toys can be obtained from second-hand cargoes of separate parts, but it requires solving an order-picking problem where the primary guideline is that pieces could fit together. This is a common concern of logistical applications with limited resources. In general, providers of this type of service implement a handmade routing system in which a route is selected based on the pieces and customization required. Using this system, it is difficult to generate effective routes to pick-up pieces; for example, in many situations, the same routes are used for a long time, and new provisions on traffic behavior or new routes available to ensure the correct supply of each piece are not considered. In this chapter, the authors propose an amalgam model using case-based reasoning and an algorithm based on the behavior of birds to solve the problem.