Petri Net Decomposition Approach to Optimization of Route Planning Problems for AGV Systems

Abstract

In this paper, we propose a Petri Net (PN) decomposition approach to the optimization of route planning problems for automated guided vehicles (AGVs) in semiconductor fabrication bays. An augmented PN is developed to model the concurrent dynamics for multiple AGVs. The route planning problem to minimize the total transportation time is formulated as an optimal transition firing sequence problem for the PN. The PN is decomposed into several subnets such that the subnets are made independent by removing the original shared places and creating its own set of resource places for each subnet with the appropriate connections. The partial solution derived at each subnet is not usually making a feasible solution for the entire PN. The penalty function algorithm is used to integrate the solutions derived at the decomposed subnets. The optimal solution for each subnet is repeatedly generated by using the shortest-path algorithm in polynomial time with a penalty function embedded in the objective function. The effectiveness of the proposed method is demonstrated for a practical-sized route planning problem in semiconductor fabrication bay from computational experiments. Note to Practitioners-For rapid growth of transportation systems for semiconductor fabrication bay, it is required to generate a collision-free route planning for multiple AGVs efficiently to minimize the total traveling time. Conventional decomposition tech-niques for mathematical programming need reformulation of the original problem when new constraints are added, that makes it extremely difficult to modify the optimization model. PNs can be used as a tool to integrate modeling, simulation, and optimization for designing transportation systems. This paper presents a modeling and optimization of route planning for multiple AGVs by PN. The main difficulty for optimization is the state explosion for PN. To reduce computational complexity, we propose a PN decomposition approach for solving large-scale optimization problems efficiently. The PN model is partitioned into several decomposed subnets. The local solutions of the subnets are integrated by the novel optimization algorithm. The shorter computation time by the proposed method enables us to use the proposed methodology for the rapid design and dynamic optimization for AGVs transportation systems in semiconductor manufacturing.

FMS Scheduling under Availability Constraint with Supervisor Based on Timed Petri Nets

“…In addition, the efficiency of our approach could also be highlighted by the fact that [21] assume that the order of jobs could differ in machines (more relaxed). [10,13]; [20,23]; [30,35]; [41,43] …”

“…Several decomposition methods for Petri net variants have been developed [29]. Nishi et al [30,31] proposed a general PN decomposition method and coordination algorithm in order to optimize the conflict-free routing for an Automated Guided Vehicle (AGV). Ciardo et al [32] introduced the concepts of near independence and near decomposition where the authors developed an approach for the solution of stochastic Petri net models.…”

Automated guided vehicle mission reliability modelling using a combined fault tree and Petri net approach

“…However, to date the Petri net (PN) method has only been used as a mathematical tool to investigate route planning and control strategies for AGV systems. For example, Luo and Ni [21] designed a programmable logical controller (PLC) using Petri nets to prevent collisions of vehicles in an AGV system and Nishi and Maeno [22] proposed an approach to optimise the routing planning for AGVs in semiconductor fabrication bays.…”

Model reformulation for conflict-free routing problems using Petri Net and Deterministic Finite Automaton

“…First are the operational research approaches such as the set partitioning formulation [5] and colony optimization [6]. Second are the discrete-event model approaches in which several studies are using Petri Net (PN) [2,7]. Third are the control theory approaches [8][9][10], which this paper belongs to.…”