the research interests of dr. andreas bortfeldt focus on advanced methods for decision support like graph search strategies and metaheuristics, including also parallel metaheuristics. new approaches are developed in the first line for cutting and packing problems of different types and dimensions. recently highly topical problems in the area of transportation logistics which combine packing and routing aspects are investigated. moreover, other application fields, e.g., container management in seaports or school timetabling, are also addressed. further research activities are concerned with the development of patterns for object oriented system analysis. current research projects are dealing with:
• the development of metaheuristics for solving different vehicle routing and three-dimensional loading problems
• the development of a graph search approach for three-dimensional container loading that is capable to take into account a broad spectrum of packing constraints
• the development of graph search approaches for container pre-marshalling problems in container seaports
• the development of an instance generator for 3d container loading problems with multiple constraints.
vehicle routing with three-dimensional loading constraints and split pickup
the capacitated vehicle routing problem with three-dimensional loading constraints (3l-cvrp) combines vehicle routing and three-dimensional loading with additional packing constraints concerning, for example, the stability of packed goods. we consider a shanghai automotive logistics company that serves many car makers in metropolitan shanghai and whole china. the company performs milk-run operations in and around shanghai where goods are picked up at different sites by identical vehicles. often, the load of one site exceeds the volume capacity of a vehicle. therefore, we focus on the 3l-cvrp with split pickup. we propose a hybrid algorithm for this problem with two main steps. in the first step, shuttle routes, other small routes and related packing plans are calculated which serve primarily those customers who have a load that exceeds or almost reaches the volume capacity of a vehicle. in the second step, the residual problem is solved as 3l-cvrp without splits by means of a well-known solution method. the hybrid algorithm is tested by a set of instances that comes from real industrial data, with up to 46 sites and 1549 boxes to be transported. the hybrid algorithm yields good results within short computing times.