Evaluating the solution performance of IP and CP for berth allocation with time-varying water depth

This paper considers the berth allocation problem (BAP) with time-varying water depth at a tidal river port. Both integer programming (IP) and constraint programming (CP) models are developed. Numerical experiments find that CP tends to be superior to IP when the feasible domain is small (e.g. dynamic vessel arrivals), when the restriction of the objective towards decision variables is loose (e.g. makespan, departure delay), or when the size of IP models is too large due to fine time resolution. Meanwhile, CP’s incapability of proving optimality can be compensated by post-optimization with IP, by using a simple CP/IP hybrid procedure.