Abstract
This paper considers the learning/aging effect in an n job single machine scheduling problem with common due date. The objective is to determine the optimal common due date and the optimal sequence of jobs that minimizes a cost function in the presence of learning/aging effect. The cost function depends on the individual job earliness and tardiness values; i.e., ∑ j = 1 n { E [ j ] + T [ j ] } . This is a well-known problem when the learning/aging effect is not considered and it is shown in earlier studies that there are more than one optimal sequence and optimal common due dates. It is shown in earlier studies that there are 2 r - 1 optimal sequences to this problem if n is odd, and 2 r optimal sequences if n is even. The value of r is ( n + 1 ) / 2 if n is odd, and the value of r is n / 2 if n is even. In this paper, we derive two bounds B α and B α * for the learning index α . We show that when B α < α < 0 , then the optimal sequence is unique and provide an O ( n log n ) algorithm to obtain this unique optimal sequence and the optimal common due date. We also show that when α < B α * , the optimal sequence is obtained by arranging the longest job in first position and the rest of the jobs in SPT order. Similarly, we derive two bounds A α and A α * for the aging index α . We show that when 0 < α < A α , then the optimal sequence is unique and provide an O ( n log n ) algorithm to obtain this unique optimal sequence and the optimal common due date. We also show that when α > A α * , the optimal sequence is obtained by arranging the jobs in LPT order. We also present a numerical example for ease of understanding.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.