Solution Representations and Local Search for the bi-objective Inventory Routing Problem
This work addresses a specific optimization problem in logistics, but it is incremental as it builds on existing metaheuristic approaches without introducing a new paradigm.
The paper tackled the challenge of solving the bi-objective Inventory Routing Problem by investigating solution representations and local search, finding that two encodings have distinct advantages and drawbacks through experimental comparison.
The solution of the biobjective IRP is rather challenging, even for metaheuristics. We are still lacking a profound understanding of appropriate solution representations and effective neighborhood structures. Clearly, both the delivery volumes and the routing aspects of the alternatives need to be reflected in an encoding, and must be modified when searching by means of local search. Our work contributes to the better understanding of such solution representations. On the basis of an experimental investigation, the advantages and drawbacks of two encodings are studied and compared.