Single machine common flow allowance group scheduling with learning effect and resource allocation. (January 2020)

• Record Type: Journal Article
• Authors: Sun, Li; Yu, Andrew Junfang; Wu, Bin
• Is Part Of: Computers & industrial engineering. Volume 139(2020)
• Publication Date: 2020-01
• Subjects: Scheduling -- Resource allocation -- Group technology -- Common flow allowance -- Learning effect; Engineering -- Data processing -- Periodicals; Industrial engineering -- Periodicals; 620.00285
• DOI: 10.1016/j.cie.2019.106126
• Languages: English
• ISSNs: 0360-8352

Abstract

Highlights: A group scheduling with learning effects and resource allocation. Considering individual due dates based on a common flow allowance. Formulating the decision model for the optimal job sequence by assignment problem approach. Giving the polynomial time algorithm for the solution. Abstract: We introduce a single-machine group scheduling job-dependent due date assignment problem with learning effects and resource allocation in which each job is assigned an individual due date based on a common flow allowance. The actual processing time of a job depends not only on its scheduled position but also on its resource allocation. A job completed earlier (later) than its due date will incur an earliness (tardiness) penalty. Our goal is to find the optimal sequence for both the groups and jobs, together with the optimal due date assignment and the optimal resource allocation to minimize the total cost that comprises the earliness and tardiness penalties, and common flow allowance and resource allocation. We give polynomial time algorithm to solve these problems.