46. Job shop scheduling problem with a dual-gripper robot
Invited abstract in session WA-20: Topics in Combinatorial Optimization 3, stream Combinatorial Optimization.
Wednesday, 8:30-10:00Room: Esther Simpson 2.11
Authors (first author is the speaker)
| 1. | Wei Wang
|
| College of Management and Economics, Tianjin University | |
| 2. | Zhaofang Mao
|
| Tianjin University |
Abstract
Robots are increasingly being deployed as integral material-handling components within automated manufacturing systems. In this paper, we address the scheduling problem in a bufferless job shop environment. The system processes multiple job types, all served by a dual-gripper robot. The dual-gripper robot is capable of holding two jobs simultaneously but can load or unload only one job at a time. We also consider the time required for the robot to switch grippers. The objective is to determine both the robot's transport sequence and the job processing sequence to minimize the makespan. We formulate a mixed-integer linear programming (MILP) model that minimizes the makespan. Due to the complexity of the problem, we develop an improved simulated annealing algorithm (ISA). Extensive computational experiments are conducted to evaluate the performance of both the MILP and ISA, and the results confirm the superiority of the ISA compared to the MILP and other heuristic algorithms.
Keywords
- Scheduling
- Combinatorial Optimization
- Algorithms
Status: accepted
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