This work introduces a fuzzy optimization model, which solves in an integrated way the berth allocation problem (BAP) and quay crane (QCAP). The is solved for multiple quays, considering vessels’ imprecise arrival times. model optimizes use of quays. BAP + QCAP, NP-hard (Non-deterministic polynomial-time hardness) combinatorial problem, where decision to assign available quays each vessel adds ...

Decision support systems and automated planning have become essential for the effective management of seaport container terminals. Due to ever-increasing levels maritime traffic freight transportation, terminals are expected facilitate their intra-yard operations while respecting tighter vessel schedules. Employed models must therefore be capable providing berth allocation decisions which not o...

The continuous berth allocation and quay crane assignment problem considers the size of berths ships, number cranes, dynamic ships non-crossing constraints cranes. In this work, a mixed-integer linear programming model is established, aiming at minimizing total stay time delay penalty ships. To solve model, separated into discrete segments via proposed discretization strategy. Thereafter, large...

In this paper, the optimization of the Berth Allocation Problem (BAP) is transformed into a multiple stage decision making procedure and a new multiple stage search method, namely stochastic beam search algorithm, is proposed to solve it. New techniques such as an improved beam search scheme, a two-phase node goodness estimation, and a stochastic node selection criteria are proposed. Real-life ...

Decision makers must face the dynamism and uncertainty of real-world environments when they need to solve the scheduling problems. Different incidences or breakdowns, for example, initial data could change or some resources could become unavailable, may eventually cause the infeasibility of the obtained schedule. To overcome this issue, a robust model and a proactive approach are presented for ...