Solving a stochastic berth allocation problem using a hybrid sequence pair-based simulated annealing algorithm

2018 ◽  
Vol 51 (10) ◽  
pp. 1810-1828 ◽  
Author(s):  
Mohammad Mohammadi ◽  
Kamran Forghani
Keyword(s):  
Simulated Annealing ◽  
Simulated Annealing Algorithm ◽  
Allocation Problem ◽  
Berth Allocation ◽  
Sequence Pair ◽  
Berth Allocation Problem ◽  
Hybrid Sequence ◽  
Annealing Algorithm

A New Memetic Approach to Solve the Strategic Berth Template Problem

2021 ◽  
Vol 12 (3) ◽  
pp. 212-231
Author(s):  
Issam El Hammouti ◽  
Azza Lajjam ◽  
Mohamed El Merouani
Keyword(s):  
Large Scale ◽  
Container Terminal ◽  
Mathematical Formulation ◽  
Population Based ◽  
Allocation Problem ◽  
Computational Time ◽  
Berth Allocation ◽  
Berth Allocation Problem ◽  
Simulating Annealing ◽  
Annealing Algorithm

The berth allocation problem is one of the main concerns of port operators at a container terminal. In this paper, the authors study the berth allocation problem at the strategic level commonly known as the strategic berth template problem (SBTP). This problem aims to find the best berth template for a set of calling ships accepted to be served at the port. At strategic level, port operator can reject some ships to be served for avoid congestion. Since the computational complexity of the mathematical formulation proposed for SBTP, solution approaches presented so far for the problem are limited especially at level of large-scale instances. In order to find high quality solutions with a short computational time, this work proposes a population based memetic algorithm which combine a first-come-first-served (FCFS) technique, two genetics operators, and a simulating annealing algorithm. Different computational experiences and comparisons against the best known solutions so far have been presented to show the performance and effectiveness of the proposed method.

An Extended Simulated Annealing Based on the Memory Structure to Solve Redundancy Allocation Problem

2019 ◽  
Vol 18 (04) ◽  
pp. 527-548
Author(s):  
Arash Zaretalab ◽  
Vahid Hajipour
Keyword(s):  
Simulated Annealing ◽  
Simulated Annealing Algorithm ◽  
Heuristic Algorithms ◽  
Optimization Problems ◽  
Solution Space ◽  
Global Optimum ◽  
Allocation Problem ◽  
Redundancy Allocation Problem ◽  
Redundancy Allocation ◽  
Annealing Algorithm

One of the most practical optimization problems in the reliability field is the redundancy allocation problem (RAP). This problem optimizes the reliability of a system by adding redundant components to subsystems under some constraints. In recent years, various meta-heuristic algorithms applied to find a local or global optimum solution for RAP in which redundancy strategies are chosen. Among these algorithms, simulated annealing algorithm (SA) is a capable one and makes use of a mathematical analogue to the physical annealing process to finding the global optimum. In this paper, we present a new simulated annealing algorithm named knowledge-based simulated annealing (KBSA) to solve RAP for the series-parallel system when the redundancy strategy can be chosen for individual subsystems. In the KBSA algorithm, the SA part searches the solution space to find good solutions and knowledge model saves the knowledge of good solution and feed it back to the algorithm. In this paper, this approach achieves the optimal result for some instances in the literature. In order to evaluate the performance of the proposed algorithm, it is compared with well-known algorithms in the literature for different test problems. Finally, the results illustrate that the proposed algorithm has a good proficiency in obtaining desired results.

scholarly journals Berth Allocation Optimization with Priority based on Simulated Annealing Algorithm

2018 ◽  
Vol 11 (1) ◽  
pp. 74-83
Author(s):  
Wang Yuping ◽  
◽  
Hao Yangyang ◽  
Zhang Yuanhui ◽  
Gu Tianyi ◽  
...  
Keyword(s):  
Simulated Annealing ◽  
Simulated Annealing Algorithm ◽  
Berth Allocation ◽  
Annealing Algorithm
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