Cyclic job shop robotic cell scheduling problem: Ant colony optimization. (September 2017)

• Record Type: Journal Article
• Authors: Elmi, Atabak; Topaloglu, Seyda
• Is Part Of: Computers & industrial engineering. Volume 111(2017)
• Page Start: 417
• Page End: 432
• Publication Date: 2017-09
• Subjects: Scheduling -- Robotic cell -- Cyclic job shop -- Multiple robots; Engineering -- Data processing -- Periodicals; Industrial engineering -- Periodicals; 620.00285
• DOI: 10.1016/j.cie.2017.08.005
• Languages: English
• ISSNs: 0360-8352

Abstract

Highlights: This research studies cyclic job shop robotic cell scheduling problem. Multiple single gripper robots are considered to perform transportation operations. An ACO based algorithm is proposed to minimize the cycle time. The characteristics of the considered problem are stated by an instance problem. The proposed algorithm finds the appropriate height of jobs for the considered problem. Abstract: This paper deals with the cyclic job shop robotic cell scheduling problem with multiple robots. All the jobs are processed in order of their operations on multiple machines with standard processing times and the single gripper robots perform the transportation operations of jobs between the machines. Due to the special characteristics of the considered problem and NP-hard computational complexity, a metaheuristic algorithm based on ant colony optimization has been proposed. The proposed algorithm simultaneously determines the optimal height of jobs in the cyclic schedule, the robot assignments for transportation operations, and the optimal sequencing of the robots moves, which in return maximize the throughput rate. The efficiency of the proposed model is examined by a computational study on a set of randomly generated problem instances.