Dispatching of multiple Autonomous Intelligent Vehicles considering stochastic travel times by Genetic Algorithm

An assumption on deterministic travel times of the vehicles might not be realistic for the dispatching problem of multiple Autonomous Intelligent Vehicles (AIVs). Thus, this paper presents a more accurate approach to solve this problem by considering stochastic travel times of the vehicles. The problem is modeled as a stochastic combinatorial optimization (SCO) problem that aims to minimize the total travel time and balance the utilization time of AIVs. Genetic Algorithm (GA) is then used to provide near-optimal solutions for the SCO. The obtained near-optimal results are then compared with the ones using conventional ruled-based approaches. The results showed that the GA solver could outperform the conventional ruled-based approaches in both deterministic and stochastic testing scenarios.

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