Scheduling with job-dependent past-sequence-dependent setup times and job-dependent position-based learning effects on a single processor
by H.M. Soroush
European J. of Industrial Engineering (EJIE), Vol. 9, No. 3, 2015

Abstract: Scheduling with setup time and learning is of importance in today's manufacturing and service organisations where reliable and low cost products/services should be delivered on time. This paper addresses the problem of scheduling jobs on a single processor (or machine) where the setup times are job-dependent and past-sequence-dependent (psd), and the learning effects are job-dependent and position-based. The goal is to minimise each of the objective functions: the sum of the ρ^th (ρ ≥ 0) powers of completion times, the maximum lateness, the maximum tardiness, the total tardiness, the total weighted completion time when the weights are non-linear functions of job positions, and the total absolute differences in waiting times. Special cases of the resulting problems are solvable polynomially. For the general cases, we introduce heuristic approaches to approximate the solutions with respect to the first four objectives, and extend the branch-and-bound (B&B) methods of Soroush (2012) to derive the optimal sequences with respect to the last two objectives. Computational results show that the proposed heuristics perform well and the solution times of B&Bs are reasonable. [Received 13 July 2013; Revised 30 December 2013; Accepted 21 February 2014]

Online publication date: Wed, 13-May-2015

The full text of this article is only available to individual subscribers or to users at subscribing institutions.

 
Existing subscribers:
Go to Inderscience Online Journals to access the Full Text of this article.

Pay per view:
If you are not a subscriber and you just want to read the full contents of this article, buy online access here.

Complimentary Subscribers, Editors or Members of the Editorial Board of the European J. of Industrial Engineering (EJIE):
Login with your Inderscience username and password:

Username:        Password:          Forgotten your password?

Want to subscribe?
A subscription gives you complete access to all articles in the current issue, as well as to all articles in the previous three years (where applicable). See our Orders page to subscribe.

If you still need assistance, please email subs@inderscience.com