Online scheduling on parallel-batch machines with periodic availability constraints and job delivery. (April 2023)

• Record Type: Journal Article
• Authors: Lin, Ran; Wang, Jun-Qiang; Oulamara, Ammar
• Is Part Of: Omega. Volume 116(2023)
• Publication Date: 2023-04
• Subjects: Online scheduling -- Batch machines -- Availability constraint -- Competitive ratio; Management -- Periodicals; 658.4005
• DOI: 10.1016/j.omega.2022.102804
• Languages: English
• ISSNs: 0305-0483

Abstract

Highlights: Propose the online batch scheduling problem with availability constraints and job delivery. Consider objectives: maximum flow time, maximum delivery time and total flow time. Design the online algorithms for the three objectives. Analyze the lower bounds on competitive ratios for the online problems. Show the competitive ratios of the online algorithms. Abstract: We address an online scheduling problem on identical parallel-batch machines with periodic availability constraints and job delivery. A parallel-batch machine can process several jobs simultaneously in a batch without any preemption. The processing time of a batch is equal to the maximum processing time of the jobs in this batch, and the job processing times we consider are identical on all machines. Available and unavailable time intervals occur alternately on machines. The unavailable time intervals have the same start and end time on different machines. Jobs are released over time, which means that no information of the job is known in advance before its release date. After completion, job is delivered to customer. Three objective functions, namely, maximum flow time, maximum delivery time and total flow time are considered separately. For these objectives, we derive lower bounds on competitive ratios, provide online algorithms and analyze their competitive ratios.