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Axon Stretch Growth: The Mechanotransduction of Neuronal Growth
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Modified NSGA-II for Solving Continuous Berth Allocation Problem: Using Multiobjective Constraint-Handling Strategy.

Bin Ji, Xiaohui Yuan, Yanbin Yuan

    IEEE Transactions on Cybernetics
    |March 3, 2017
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    Summary
    This summary is machine-generated.

    This study optimizes ship scheduling for the continuous berth allocation problem (BAPC) by transforming it into a multiobjective problem. A novel algorithm, MNSGA-II, effectively minimizes port stay time and handles complex constraints.

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    Area of Science:

    • Transportation Engineering
    • Operations Research
    • Computer Science

    Background:

    • The continuous berth allocation problem (BAPC) is a critical optimization challenge in maritime logistics.
    • Existing heuristic methods for BAPC struggle with complex constraints, often leading to suboptimal solutions.
    • The NP-hard nature of BAPC necessitates advanced optimization techniques.

    Purpose of the Study:

    • To reformulate the constrained single-objective BAPC (SBAPC) into an unconstrained multiobjective BAPC (MBAPC) model.
    • To introduce a novel optimization algorithm, a bias selection modified non-dominated sorting genetic algorithm II (MNSGA-II), for solving the MBAPC.
    • To evaluate the effectiveness of the MBAPC model and the MNSGA-II algorithm against existing methods.

    Main Methods:

    • Transformation of SBAPC into MBAPC by treating constraint violation as an objective.
    • Development and application of a modified non-dominated sorting genetic algorithm II (MNSGA-II) with a bias selection mechanism.
    • Utilizing an archive within MNSGA-II to guide the search towards feasible solutions.

    Main Results:

    • The MBAPC model demonstrated feasibility in representing the berth allocation problem.
    • The MNSGA-II algorithm achieved superior performance compared to other multiobjective optimization algorithms.
    • MNSGA-II outperformed single-objective methods when applied to the SBAPC model.

    Conclusions:

    • The MBAPC model provides a viable framework for addressing the complexities of berth allocation.
    • The MNSGA-II algorithm offers significant advantages in optimizing ship scheduling and minimizing port operations time.
    • This research contributes a more effective approach to solving the continuous berth allocation problem.