One of the port planning problems that has been noticed in many papers and research is the berth planning problems. Berth planning includes two sub-problems; Berth Allocation Problem (BAP) and Quay Crane Assignment Problem (QCAP). This paper develops one mathematical model by integrating these two sub-problems. The berth allocation and quay crane assignment model (BAQCAP) is solved by two metaheuristic algorithms; Taboo Search (TS) and Ant Colony Optimization (ACO). On the other hand, the berth plan is located in a disturbed environment; unexpected events may occur during the execution of the plan, making it infeasible or challenging to do the initial berth plan. These unexpected events are known as disruptions, which can impose additional costs on the port or make the initial berth plan infeasible. For this reason, The primary purpose of this paper is on the berth plan recovery in the disrupted situation. the Berth plan is recovered with two methods; Global recovery and local recovery. This paper compares global and local recovery to identify the optimal method for berth plan recovery. The numerical results show the optimal performance in the local recovery method. In this paper, the data from Shahid Rajaei port is used.

Ideal cascades for binary mixtures of isotopes are specified by no-mixing at confluent points and minimum total flows. Studies show that there is another type of cascade called an optimum cascade. These cascades have total flows lower than ideal cascades while separation factors are greater than unity and mixings are allowed. In this paper, using a Co-Evolutionary Particle Swarm Optimization (CPSO) algorithm, the ideal and optimum cascades are compared in different operating regimes. The CPSO is a metaheuristic algorithm that uses the concept of co-evolution to deal with constrained engineering Optimization problems. In this study, it is used to find the parameters of the optimum cascade. In this work, three test cases are considered to compare ideal and optimum cascades. The first test case includes two distinct symmetrical separation cascades. In the first cascade, the minimum total flow for the ideal type 3 cascade and its corresponding optimum cascade is obtained as ∑L⁄P=176. 7128, and in the second one for the ideal type 1 cascade and its corresponding optimum cascade, it is obtained as ∑L⁄P=202. 7828. The results show that for symmetric separation, the ideal cascade coincides with the optimum cascade. In test case 2, the minimum total flows for the ideal type 1 cascade of non-symmetrical separation elements and its corresponding optimum cascade (CPSO) are obtained as ∑L⁄P=477. 6170 and ∑L⁄P=228. 6997, respectively. In test case 3, for the ideal type 2 cascade of non-symmetrical elements and its corresponding optimum cascade, the minimum total flows are obtained as ∑L⁄P=299. 99 and ∑L⁄P=191. 6584, respectively.