An efficient heuristic for adaptive production scheduling and control in one-of-a-kind production
MetadataShow full item record
Even though research in flow shop production scheduling has been carried out for many decades, there is still a gap between research and applicationespecially in manufacturing paradigms such as one-of-a-kind production (OKP) that intensely challenges real time adaptive production scheduling and control. Indeed, many of the most popular heuristics continue to use Johnson's algorithm (1954) as their core. This paper presents a state space (SS) heuristic, integrated with a closed-loop feedback control structure, to achieve adaptive production scheduling and control in OKP. Our SS heuristic, because of its simplicity and computational efficiency, has the potential to become a core heuristic. Through a series of case studies, including an industrial implementation in OKP, our SS-based production scheduling and control system demonstrates significant potential to improve production efficiency. © 2010 Elsevier Ltd. All rights reserved.
Showing items related by title, author, creator and subject.
Nandong, Jobrun (2010)The vast majority of chemical and bio-chemical process plants are normally characterized by large number of measurements and relatively small number of manipulated variables; these thin plants have more output than input ...
Nordin, Syarifah Zyurina (2011)Task scheduling in parallel processing systems is one of the most challenging industrial problems. This problem typically arises in the manufacturing and service industries. The task scheduling problem is to determine a ...
Fava, L.; Millar, D.; Maybee, Bryan (2011)The Schedule Optimisation Tool (SOT) is a software that identifies the sequence (schedule) of mine development and the ore production activities that maximise the Net Present Value (NPV). A case study exercise in a live ...