Comparison of simulated annealing and tabu-search algorithms in advanced planning and scheduling systems for TFT-LCD colour filter fabs

2016 ◽  
Vol 30 (6) ◽  
pp. 516-534 ◽  
Author(s):  
James C. Chen ◽  
Yin-Yann Chen ◽  
Tzu-Li Chen ◽  
Jim Z. Lin
Keyword(s):  
Simulated Annealing ◽  
Tabu Search ◽  
Search Algorithms ◽  
Colour Filter ◽  
Planning And Scheduling ◽  
Advanced Planning And Scheduling ◽  
Advanced Planning

SIMULATED ANNEALING AND TABU SEARCH ALGORITHMS FOR MULTIWAY GRAPH PARTITION

1992 ◽  
Vol 02 (02) ◽  
pp. 159-185 ◽  
Author(s):  
L. TAO ◽  
Y.C. ZHAO ◽  
K. THULASIRAMAN ◽  
M.N.S. SWAMY
Keyword(s):  
Experimental Study ◽  
Simulated Annealing ◽  
Tabu Search ◽  
Time Frame ◽  
Search Algorithms ◽  
Graph Partition ◽  
Solution Quality ◽  
Running Time ◽  
New Algorithms

For a given graph G with vertex and edge weights, we partition the vertices into subsets to minimize the total weights for edges crossing the subsets (weighted cut size) under the constraint that the vertex weights are evenly distributed among the subsets. We propose two new effective graph partition algorithms based on simulated annealing and tabu search, and compare their performance with that of the LPK algorithm reported in Ref. 12. Extensive experimental study shows that both of our new algorithms produce significantly better solutions than the LPK algorithm (maximal and minimal improvements on average weighted cut size are roughly 51.8% and 10.5% respectively) with longer running time, and this advantage in solution quality would not change even if we run the LPK algorithm repeatedly with random initial solutions in the same time frame as required by our algorithms.

scholarly journals A Constraint Programming Method for Advanced Planning and Scheduling System with Multilevel Structured Products

2014 ◽  
Vol 2014 ◽  
pp. 1-7 ◽  
Author(s):  
Yunfang Peng ◽  
Dandan Lu ◽  
Yarong Chen
Keyword(s):  
Constraint Programming ◽  
Programming Model ◽  
Computational Study ◽  
Constraint Propagation ◽  
Mixed Integer ◽  
Release Time ◽  
Planning And Scheduling ◽  
Structured Products ◽  
Advanced Planning And Scheduling ◽  
Advanced Planning

This paper deals with the advanced planning and scheduling (APS) problem with multilevel structured products. A constraint programming model is constructed for the problem with the consideration of precedence constraints, capacity constraints, release time and due date. A new constraint programming (CP) method is proposed to minimize the total cost. This method is based on iterative solving via branch and bound. And, at each node, the constraint propagation technique is adapted for domain filtering and consistency check. Three branching strategies are compared to improve the search speed. The results of computational study show that the proposed CP method performs better than the traditional mixed integer programming (MIP) method. And the binary constraint heuristic branching strategy is more effective than the other two branching strategies.

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