ORNInA: A decentralized, auction-based multi-agent coordination in ODT systems

On-Demand Transport (ODT) systems have attracted increasing attention in recent years. Traditional centralized dispatching can achieve optimal solutions, but NP-Hard complexity makes it unsuitable for online and dynamic problems. Centralized decentralized heuristics fast, feasible solution at run-time with no guarantee on the quality. Starting from a not solution, we present this paper new model (ORNInA) consisting of two parallel coordination processes. The first one is insertion-heuristic based algorithm to build vehicle schedules order solve particular case Dial-A-Ride-Problem (DARP) as an ODT system, which vehicles communicate via Vehicle-to-vehicle communication (V2V) make decisions. second scheme continuous optimization process namely Pull-demand protocol, combinatorial auctions, improve quality global achieved by decision exchanging resources between (k-opt). In its simplest implementation, k set 1 so that exchange only resource time. We evaluate analyze promising results our contributed techniques synthetic data taxis operating Saint-Étienne city, against classical greedy approach uses mixed-integer linear program (MILP) solver.