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ICRA
1998
IEEE
142views Robotics» more  ICRA 1998»
13 years 9 months ago
Lagrangian Relaxation Neural Networks for Job Shop Scheduling
Abstract--Manufacturing scheduling is an important but difficult task. In order to effectively solve such combinatorial optimization problems, this paper presents a novel Lagrangia...
Peter B. Luh, Xing Zhao, Yajun Wang
ICRA
1995
IEEE
140views Robotics» more  ICRA 1995»
13 years 8 months ago
A More Efficient lagrangian Relaxation Approach to Job-Shop Scheduling Problems
Haoxun Chen, Chengbin Chu, Jean-Marie Proth
IJCNN
2006
IEEE
13 years 10 months ago
Job-Shop Scheduling with an Adaptive Neural Network and Local Search Hybrid Approach
— Job-shop scheduling is one of the most difficult production scheduling problems in industry. This paper proposes an adaptive neural network and local search hybrid approach fo...
Shengxiang Yang
ICRA
1999
IEEE
114views Robotics» more  ICRA 1999»
13 years 9 months ago
An Effective Method to Reduce Inventory in Job Shops
Inventory plays a major role in deciding the overall manufacturing costs, and a good scheduling system should balance the on-time delivery of products versus low work-in-process (W...
Peter B. Luh, Xiaohui Zhou, Robert N. Tomastik
MP
2002
85views more  MP 2002»
13 years 4 months ago
From fluid relaxations to practical algorithms for job shop scheduling: the makespan objective
We design an algorithm, called the fluid synchronization algorithm (FSA), for the job shop scheduling problem with the objective of minimizing the makespan. We round an optimal sol...
Dimitris Bertsimas, Jay Sethuraman