Introduction The berth and allocation problem is experienced during the distribution of dock space for ships in container terminuses. When ships dock at the terminuses, the terminal operators are required to allocate the vessels to specific berths to be attended within the shortest time possible. Several factors influence the selection of the dock and the time allocated for each ship. Choices on the quay crane tasks and planning are made autonomously. Nevertheless, the effectiveness of container terminus can be enhanced when the choices are made concurrently owing to the interrelation between quay crane tasks and preparation. There are several kinds of literature explaining the berth and allocation problem. The literature illustrates the different methods of solving the issue. A number of these methods emphasize on (SBAP) static berth allocation problem. Other methods concentrate on (DBAP) dynamic berth allocation problem. The above methods vary concerning the quay design utilized. The design is discrete, constant, or hybrid. Illustrated below is a literature review of six articles focusing on the berth allocation problem. Literature review Fu and Tsai offer a new method to examine the incorporated (QCASP) quay crane assignment and scheduling problem (Fu & Tsai 6959). The scholars assert that the challenge defines the task of quay cranes to containers and the order of chores to be administered by each quay crane concurrently. The incorporated challenge is problematic to resolve with precise approaches owing to its intricacy. Thus, Fu and Tsai offer a genetic algorithm called GA. They expect GA to address the incorporated QCASP (Fu & Tsai 6960). Their computational outcomes confirm the performance of the recommended GA. According to Fu & Tsai, the model has taken into account real-world restraints such as security margins and QC arrangement. Chen, Der-Horng, and Mark present an analysis of unidirectional group-based QCSP (Chen, Der-Horngee, & Mark 198). They propose that an alternative method for solving the above problem. The method seeks to address the group-based quay crane scheduling difficulty, which force dock cranes to travel in the unidirectional bearing during their preparation. Likened with other MIP prototypes for the group-based QCSP, the proposed prototype is effective because it only contains a minute group of twofold decision variables. To assess the operation of the suggested MIP prototype, Chen carried out wide-ranging arithmetical trials to evaluate the quality of the QCSP resolution approaches (Chen, Der-Horngee, & Mark 199). Concerning the trial outcomes, the suggested approach outpaces the LTM algorithm advanced by Legato. Diabat and Effrosyni recommend a cohesive prototype for the QCAP and the QCSP (Diabat & Effrosyni 115). Their model allocates hoists to ships docked in a particular planning horizon. The most significant attribute of the above prototype is the incorporation of the task and planning problem for quay cranes, which produces superior outcomes than addressing these problems autonomously. Furthermore, the prototype precisely chooses the hoist to be assigned to a particular bay (Diabat & Effrosyni 116). Through this, the pro