Abstract | ||
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Purpose - The purpose of this paper is to develop an efficient method for solving a vehicle scheduling problem (VSP) in 2D industrial environments. An autonomous vehicle is requested to serve a set of work centers in the shop floor providing transport and delivery tasks while avoiding collisions with obstacles during its travel. The objective is to find a minimum in length, collision-free vehicle routing schedule that serves timely as many as possible work centers in the shop floor.Design/methodology/approach - First, the vehicle's environment is mapped into a 2D B-Spline surface embedded in 3D Euclidean space using a robust geometric model. Then, a modified genetic algorithm is applied on the generated surface to search for an optimum legal route schedule that satisfies the requirements of the vehicle's mission.Findings - Simulation experiments show that the method is robust enough and can determine in a reasonable computation time a solution to VSP under consideration.Originality/value - There is a gap in the literature for methods that face VSP in shop-floor environments. This paper contributes to filling this gap by implementing a practical method that can be easily programmed and included in a modern service delivery system. |
Year | DOI | Venue |
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2009 | 10.1108/01439910910932630 | INDUSTRIAL ROBOT-THE INTERNATIONAL JOURNAL OF ROBOTICS RESEARCH AND APPLICATION |
Keywords | Field | DocType |
Remote control systems, Algorithmic languages, Shopfloor, Remote handling devices, Programming and algorithm theory | Teleoperation,Vehicle routing problem,Job shop scheduling,Remote control,Simulation,Scheduling (computing),Flow shop scheduling,Autonomous system (mathematics),Engineering,Genetic algorithm | Journal |
Volume | Issue | ISSN |
36 | 2 | 0143-991X |
Citations | PageRank | References |
5 | 0.55 | 13 |
Authors | ||
3 |
Name | Order | Citations | PageRank |
---|---|---|---|
Elias k. Xidias | 1 | 53 | 7.16 |
Andreas C. Nearchou | 2 | 173 | 14.97 |
Nikos A. Aspragathos | 3 | 243 | 37.69 |