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3751. Scheduling AGVs based on partial charging policy to minimize the total tardiness
Invited abstract in session WB-56: Advancing mobility towards sustainable solutions IV, stream Transportation.
Wednesday, 10:30-12:00Room: S04 (building: 101)
Authors (first author is the speaker)
| 1. | Mengxin Zhang
|
| Industrial Engineering, Southeast Univercity | |
| 2. | Hui Sun
|
| Industrial Engineering, Southeast University |
Abstract
This study addresses a problem of scheduling automated guided vehicles (AGVs), in which a fleet of heterogenous AGVs are used to deliver materials in a flexible manufacturing environment. During the transportation process, the batteries of AGVs can be recharged so that materials are delivered timely to various workstations without interruptions. A partial charging policy which enables flexible management of charging operations is applied. By effectively scheduling transfer jobs and potential charging operations on the AGVs, the objective is to minimize the total weighted tardiness. A mixed integer programming formulation is presented to describe the scheduling problem. A hybrid approach combining variable neighborhood search (VNS) and linear programming is developed to solve this NP-hard problem. VNS is firstly used to schedule transfer jobs on the AGV fleet without considering charging operations, based on which a linear programming model is formulated to determine the best schedule of charging operations on each AGV. Numerical experiments show that the hybrid solution procedure can solve the AGV scheduling problem effectively and efficiently.
Keywords
- Scheduling
- Programming, Mixed-Integer
- Metaheuristics
Status: accepted
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