Comparison of multiobjective evolutionary algorithms for solving the multiobjective route planning in dynamic multi-hop ridesharing

Ridesharing is considered as one of the promising solutions for dropping the consumption of fuel and reducing the congestion in urban cities, hence reducing the environmental pollution. Route planning is a key component for the success of ridesharing systems in which multiple objectives can be optimized. The multiobjective route planning problem in multi hop ridesharing is categorized as NP-complete. Multiobjective evolutionary algorithms have received a growing interest in solving the multiobjective optimization problems. In this work, we compare the behaviour of different multiobjective evolution ary algorithms for solving the multiobjective route planning in dynamic multi-hop ridesharing. Comparison results indicate that there is no single algorithm, as in literature, that wins all the tournaments regarding all the quality indicators. However, a subset of the algorithms is recommended with better quality and runtime.