Single CNC machine scheduling with controllable processing times and multiple due dates

• Published in: International journal of production research Vol. 46; no. 21; pp. 6087 - 6111
• Main Authors: Atan, Mehmet Oguz, Selim Akturk, M.
• Format: Journal Article
• Language: English
• Published: London Taylor & Francis Group 01-11-2008; Washington, DC Taylor & Francis; Taylor & Francis LLC
• Subjects: Applied sciences; Controllable processing times; Exact sciences and technology; Heuristic; Heuristics; Inventory control, production control. Distribution; Job shops; Multiple due dates; Numerical controls; Operational research and scientific management; Operational research. Management science; Order rejection; Production scheduling; Profit maximization; Scheduling; Scheduling algorithms; Scheduling, sequencing; Studies; Total weighted tardiness and earliness; Computer digital control; Hierarchical classification; Heuristics; Machining; Total weighted tardiness and earliness; Processing time; Scheduling; Multiple due dates; Flexibility; Due date; Optimization; Tooling; Rejection; Controllable processing times; Total weighted tardiness; Heuristic method; Controllability; Profit; Earliness; Order rejection; Single machine; Execution time
• ISSN: 0020-7543; 1366-588X
• DOI: 10.1080/00207540701262913

In this study, we solve the single CNC machine scheduling problem with controllable processing times. Our objective is to maximize the total profit that is composed of the revenue generated by the set of scheduled jobs minus the sum of total weighted earliness and weighted tardiness, tooling and machining costs. Customers offer multiple due dates to the manufacturer, each coming with a distinct price for the order that is decreasing as the date gets later, and the manufacturer has the flexibility to accept or reject the orders. We propose a number of ranking rules and scheduling algorithms that we employ in a four-stage heuristic algorithm that determines the processing times for each job and a final schedule for the accepted jobs simultaneously, to maximize the overall profit.