The cost-effective routing and scheduling of a fleet of multi-parcel chemical tankers represents a central
decision making process in both chemical and shipping industry. Ships designed for the transport of liquid
or gas in bulk are called tankers. Shippers seek to choose the cargos to transport and determine the
optimal route that the ship should follow to maximize its profit. Due to determining the optimal assignment
and 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 optimization
approaches. To overcome this limitation, this work introduces a new continuous time precedence-based
MILP mathematical formulation that is then embedded within a heuristic-based algorithm in order to
obtain near-optimal solutions to large-scale problems. The applicability and efficiency of the proposed
approach is illustrated by solving a real case of study corresponding to a sea-cargo shipping company
operating in South-East Asia. Computational results show notable improvements and better performance
when compared to other alternative reported solution techniques