An iterative MILP-based approach for maritime logistics and transportation of multi-parcel chemical tankers

Abstract

The cost-effective routing and scheduling of a fleet of multi-parcel chemical tankers represents a centraldecision making process in both chemical and shipping industry. Ships designed for the transport of liquidor gas in bulk are called tankers. Shippers seek to choose the cargos to transport and determine theoptimal route that the ship should follow to maximize its profit. Due to determining the optimal assignmentand routing decisions of a large set of cargos transported by a ship fleet is inherently NP-hard,real-world problems are either intractable or result in poor solutions when solved with pure optimizationapproaches. To overcome this limitation, this work introduces a new continuous time precedence-basedMILP mathematical formulation that is then embedded within a heuristic-based algorithm in order toobtain near-optimal solutions to large-scale problems. The applicability and efficiency of the proposedapproach is illustrated by solving a real case of study corresponding to a sea-cargo shipping companyoperating in South-East Asia. Computational results show notable improvements and better performancewhen compared to other alternative reported solution techniques