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An autonomous vehicle sequencing problem at intersections: A genetic algorithm approach

100%

Yan F., Dridi M., El Moudni A.

International Journal of Applied Mathematics and Computer Science

2013

tom 23

nr 1

183-200

This paper addresses a vehicle sequencing problem for adjacent intersections under the framework of Autonomous Intersection Management (AIM). In the context of AIM, autonomous vehicles are considered to be independent individuals and the traffic control aims at deciding on an efficient vehicle passing sequence. Since there are considerable vehicle passing combinations, how to find an efficient vehicle passing sequence in a short time becomes a big challenge, especially for more than one intersection. In this paper, we present a technique for combining certain vehicles into some basic groups with reference to some properties discussed in our earlier works. A genetic algorithm based on these basic groups is designed to find an optimal or a near-optimal vehicle passing sequence for each intersection. Computational experiments verify that the proposed genetic algorithms can response quickly for several intersections. Simulations with continuous vehicles are carried out with application of the proposed algorithm or existing traffic control methods. The results show that the traffic condition can be significantly improved by our algorithm.

Heuristic algorithms for optimization of task allocation and result distribution in peer-to-peer computing systems

100%

Chmaj G., Walkowiak K., Tarnawski M., Kucharzak M.

International Journal of Applied Mathematics and Computer Science

2012

tom 22

nr 3

733-748

Recently, distributed computing system have been gaining much attention due to a growing demand for various kinds of effective computations in both industry and academia. In this paper, we focus on Peer-to-Peer (P2P) computing systems, also called public-resource computing systems or global computing systems. P2P computing systems, contrary to grids, use personal computers and other relatively simple electronic equipment (e.g., the PlayStation console) to process sophisticated computational projects. A significant example of the P2P computing idea is the BOINC (Berkeley Open Infrastructure for Network Computing) project. To improve the performance of the computing system, we propose to use the P2P approach to distribute results of computational projects, i.e., results are transmitted in the system like in P2P file sharing systems (e.g., BitTorrent). In this work, we concentrate on offline optimization of the P2P computing system including two elements: scheduling of computations and data distribution. The objective is to minimize the system OPEX cost related to data processing and data transmission. We formulate an Integer Linear Problem (ILP) to model the system and apply this formulation to obtain optimal results using the CPLEX solver. Next, we propose two heuristic algorithms that provide results very close to an optimum and can be used for larger problem instances than those solvable by CPLEX or other ILP solvers.

Ograniczanie wyników

2 International Journal of Applied Mathematics and Computer Science

1 Chmaj G.

1 Dridi M.

1 El Moudni A.

1 Kucharzak M.

1 Tarnawski M.

1 Walkowiak K.

1 Yan F.

1 2013

1 2012

Wyniki wyszukiwania

An autonomous vehicle sequencing problem at intersections: A genetic algorithm approach

Heuristic algorithms for optimization of task allocation and result distribution in peer-to-peer computing systems