Levner E.,Holon Institute of Technology |
Kats V.,Institute of Industrial Mathematics |
Alcaide Lopez De Pablo D.,University of La Laguna |
Cheng T.C.E.,Hong Kong Polytechnic University
Computers and Industrial Engineering | Year: 2010
In this survey we review the current complexity status of basic cyclic scheduling models. We start with the formulations of three fundamental cyclic scheduling problems, namely the cyclic jobshop, cyclic flowshop, and cyclic project scheduling problems. We present state-of-the-art results on the computational complexity of the problems, paying special attention to recent results on the unsolvability (NP-hardness) of various cyclic problems arising from the scheduling of robotic cells. © 2010 Elsevier Ltd. All rights reserved.
Zhang W.-H.,Lanzhou University |
Yang A.-L.,Lanzhou University |
Yang A.-L.,Key Laboratory of Applied Mathematics and Complex Systems |
Wu Y.-J.,Lanzhou University |
And 2 more authors.
Computers and Mathematics with Applications | Year: 2015
Recently, Wang et al. (2013) proposed an efficient Hermitian and skew-Hermitian splitting (HSS) iteration method to approximate the solution of linear matrix equation. To further improve the efficiency of the HSS method, we in this paper establish a parameterized preconditioned HSS (PPHSS) iteration method by introducing two Hermitian positive definite preconditioners and two more different iteration parameters for the HSS method. The convergence properties of the PPHSS method used for solving linear matrix equation AXB=C are strictly analyzed and the quasi-optimal values of the iteration parameters for the PPHSS method are also derived. Numerical results demonstrate the feasibility and the efficiency of the PPHSS iteration method. © 2015 Elsevier Ltd. All rights reserved.
Kalir A.,Intel Corporation |
Zorea Y.,Manufacturing Systems Group |
Pridor A.,Institute of Industrial Mathematics |
Bregman L.,Institute of Industrial Mathematics
Computers and Industrial Engineering | Year: 2013
In semiconductor manufacturing, the process of short-term production planning requires setting clear and yet challenging and doable goals to each operation and toolset in the process flow per each product type. We demonstrate the complexity of this problem using an experimental study performed with proficient workforce, and then show how the problem can be decomposed, aggregated, and solved using sequential recurrent linear programming assignment problems. We also refer to the improvements that the proposed algorithm has achieved in practice when applied to multiple semiconductor production facilities, and discuss its efficiency and uniqueness as a fast heuristic relative to other proposed methods. © 2013 Elsevier Ltd. All rights reserved.