Smolt - a Parallel Memetic Matheuristic for Maritime Inventory Routing: Application to Fish Feed Distribution

Abstract

This paper studies a maritime inventory routing problem (MIRP) faced by fish feed suppliers responsible for distributing different types of fish feed from one or several production facilities to a number of fish farms located at sea with a given heterogeneous fleet of specialized vessels. The feed supplier needs to maintain sufficient inventory levels at the farms at all times while minimizing the distribution costs. We propose a discrete-time mixed-integer programming (MIP) model for the fish feed MIRP. Since a commercial MIP solver can only solve small problem instances, we also propose a novel matheuristic for solving real-life instances. The matheuristic employs a memetic algorithm, a metaheuristic combining a genetic algorithm with local search to decide how to route the vessels, coupled with a linear program for assigning quantities along the vessel routes. We perform a computational study on a number of realistic test instances generated using data from one of Norway’s largest fish feed suppliers. We show that the matheuristic outperforms a commercial MIP solver and can provide valuable decision support. Furthermore, we test the matheuristic on a set of general MIRP benchmark instances from the literature (MIRPLib). Despite not being specifically designed to solve these instances, the results indicate that the matheuristic can obtain high-quality solutions here as well.

Keywords: Maritime logistics, Maritime inventory routing problem, Multi-depot, Case study, heuristic