Neighborhood Search in Differential Evolution for Solving Trusted Ridesharing Problems

The lack of trust is one of the barriers that hinders the acceptance of ridesharing. In the past years, one of the hot research issue in the context of ridesharing is to enhance trust. Such trust based ridesharing problem can be described as an optimization problem in which a large number of constraints must be satisfied. Due to complexity of this optimization problem, exact methods are limited and cannot be applied. Therefore, approximate methods are usually applied to find the solutions. This problem can be solved by evolutionary algorithms. The purpose of this study is to develop an algorithm for trust based ridesharing problems by applying neighborhood search in Differential Evolution approach. We compare the proposed algorithm with other competitive algorithms. The numerical results indicate that applying neighborhood search in Differential Evolution approach leads to a more efficient solution algorithm.