The Biobjective Bike-Sharing Rebalancing Problem with Balance Intervals: A Multistart Multiobjective Particle Swarm Optimization Algorithm、

The Biobjective Bike-Sharing Rebalancing Problem with Balance Intervals is a complex optimization problem that involves balancing the distribution of bikes across different locations in a bike-sharing system. The problem requires identifying the optimal rebalancing strategy that minimizes both the number of empty and full stations while also ensuring that the balance intervals between stations are maintained.

To solve this problem, a multistart multiobjective particle swarm optimization algorithm is proposed. The algorithm uses a combination of multiple starting points and particle swarm optimization techniques to find the optimal solution. The algorithm works by initializing a set of particles at different locations in the search space and then iteratively updating their positions based on the fitness of the solutions they generate.

The algorithm also incorporates a diversity maintenance mechanism that helps to ensure that the algorithm does not get stuck in local optima. The diversity maintenance mechanism involves using a crowding distance metric to encourage the particles to explore different regions of the search space.

The proposed algorithm is tested on a set of benchmark instances and compared to several other state-of-the-art algorithms. The results show that the proposed algorithm outperforms the other algorithms on a majority of the instances, demonstrating its effectiveness in solving the Biobjective Bike-Sharing Rebalancing Problem with Balance Intervals.