Service time optimization of mixed-line flow shop systems
IEEE Transactions on Automatic Control
Please cite this item using this persistent URLhttp://hdl.handle.net/11693/22438
We consider deterministic mixed-line flow shop systems that are composed of controllable and uncontrollable machines. Arrival times and completion deadlines of jobs are assumed to be known, and they are processed in the order they arrive at the machines. We model these flow shops as serial networks of queues operating under a non-preemptive first-come-first-served policy, and employ max-plus algebra to characterize the system dynamics. Defining completion-time costs for jobs and service costs at controllable machines, a non-convex optimization problem is formulated where the control variables are the constrained service times at the controllable machines. In order to simplify this optimization problem, under some cost assumptions, we show that no waiting is observed on the optimal sample path at the downstream of the first controllable machine. We also present a method to decompose the optimization problem into convex subproblems. A solution algorithm utilizing these findings is proposed, and a numerical study is presented to evaluate the performance improvement due to this algorithm. © 2010 IEEE.
- Research Paper 
Showing items related by title, author, creator and subject.
Optimal signaling and detector design for power-constrained binary communications systems over non-Gaussian channels Göken, C.; Gezici, S.; Arikan, O. (2010)In this letter, joint optimization of signal structures and detectors is studied for binary communications systems under average power constraints in the presence of additive non-Gaussian noise. First, it is observed that ...
Alper Yildirim, E. (2012)We consider linear optimization problems over the cone of copositive matrices. Such conic optimization problems, called copositive programs, arise from the reformulation of a wide variety of difficult optimization problems. ...
Urfaliog̃lu O.; Çetin, A.E.; Kuruog̃lu, E.E. (2008)A novel evolutionary global optimization approach based on adaptive covariance estimation is proposed. The proposed method samples from a multivariate Levy Skew Alpha-Stable distribution with the estimated covariance matrix ...