Swarm intelligence in logistics and production planning

In this chapter, major contributions of swarm intelligence in the fields of logistics and production planning are discussed. Starting with a general introduction to planning problems in these fields, we outline the limitations of traditional optimization approaches and the reasons for using methods from the field of swarm intelligence such as the NP-hardness of many important problems (Section 6.1). We discuss some general aspects of utilizing swarm algorithms which can be used for optimizations problems in logistics and productions, and introduce briefly some well-established and a few newer approaches in that field (Section 6.2). After that, the most important problem types such as lot-sizing problems, scheduling problems, and vehicle routing problems are discussed including modeling aspects and results from swarm intelligence applications (Section 6.3). As a result, we see that established approaches such as particle swarm optimization and ant colony optimization are well established in these areas including various variants and improvements, which were worked out for the specific problems under consideration including hybridizations of the algorithms with other techniques. We also discuss the current situation with respect to solving such problems in real life including the future potential of including swarm intelligence in commercial solutions (Section 6.4).