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

机译：ORNINA：在ODT系统中分散，基于拍卖的多智能经纪协调

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摘要

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 and decentralized heuristics can achieve fast, feasible solution at run-time with no guarantee on the quality. Starting from a feasible not optimal solution, we present in this paper a new solution model (ORNInA ) consisting of two parallel coordination processes. The first one is a decentralized insertion-heuristic based algorithm to build vehicle schedules in order to solve a particular case of the dynamic Dial-A-Ride-Problem (DARP) as an ODT system, in which vehicles communicate via Vehicle-to-vehicle communication (V2V) and make decentralized decisions. The second coordination scheme is a continuous optimization process namely Pull-demand protocol, based on combinatorial auctions, in order to improve the quality of the global solution achieved by decentralized decision at run-time by exchanging resources between vehicles (k -opt). In its simplest implementation, k is set to 1 so that vehicles can exchange only one resource at a time. We evaluate and analyze the promising results of our contributed techniques on synthetic data for taxis operating in Saint-Étienne city, against a classical decentralized greedy approach and a centralized one that uses a classical mixed-integer linear program (MILP) solver.
机译：按需运输（ODT）系统近年来引起了不断的关注。传统的集中调度可以实现最佳解决方案，但NP-Hard Complexity使其不适合在线和动态问题。集中和分散的启发式机器可以在运行时实现快速，可行的解决方案，没有保证质量。从可行而不是最佳解决方案开始，我们在本文中存在新的解决方案模型（Ornina），由两个平行协调过程组成。第一个是分散的插入启发式基于基于算法，​​以构建车辆调度，以便解决动态拨号-A-ride-ristion（DARP）作为ODT系统的特定情况，其中车辆通过车辆到车辆进行通信通信（V2V）并进行分散的决策。第二种协调方案是一种连续优化过程，即基于组合拍卖，以提高通过在运行时通过交换车辆之间的资源（k -opt）在运行时分散决定实现的全球解决方案的质量。在其最简单的实现中，k设置为1，以便车辆一次只能交换一个资源。我们评估和分析我们对Saint-étienneCity的出租车合成数据的有前途的结果，反对经典分散的贪婪方法和使用经典混合整数线性程序（MILP）求解器的集中式。

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