Future paths for integer programming and links to artificial intelligence
Computers and Operations Research - Special issue: Applications of integer programming
The shifting bottleneck procedure for job shop scheduling
Management Science
Scheduling Algorithms
Scheduling Computer and Manufacturing Processes
Scheduling Computer and Manufacturing Processes
A genetic algorithm for the dynamic single machine scheduling problem
Proceedings of the IFIP TC5/WG5.3 Forth IFIP/IEEE International Conference on Information Technology for Balanced Automation Systems in Manufacture and Transportation: Advanced Network Enterprises, Virtual Organizations, Balanced Automation, and Systems Integration
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The planning of Manufacturing Systems involves frequently the resolution of a huge amount and variety of combinatorial optimization problems with a important impact on the performance of manufacturing organizations. The proposed approach is in line with reality and away from the approaches that deal with static and classic or basic Job-Shop scheduling problems. In fact, in real world, where problems are essentially of dynamic and stochastic nature, the traditional methods or algorithms are of very little use. This is the case with most algorithms for solving the so-called static scheduling problem for different setting of both single and multimachine systems arrangements. This reality, motivated us to concentrate on tools, which could deal with such dynamic, disturbed scheduling problems, for multi-machine manufacturing settings, even though, due to the complexity of these problems, optimal solutions may not be possible to find.