WSC '96 Proceedings of the 28th conference on Winter simulation
Self-Organization in Biological Systems
Self-Organization in Biological Systems
Simulation optimization: simulation-based optimization
Proceedings of the 34th conference on Winter simulation: exploring new frontiers
Simulation-based optimization: practical introduction to simulation optimization
Proceedings of the 35th conference on Winter simulation: driving innovation
EMF: Eclipse Modeling Framework 2.0
EMF: Eclipse Modeling Framework 2.0
Complex Scheduling (GOR-Publications)
Complex Scheduling (GOR-Publications)
Multicriteria Scheduling: Theory, Models and Algorithms
Multicriteria Scheduling: Theory, Models and Algorithms
Scheduling: Theory, Algorithms, and Systems
Scheduling: Theory, Algorithms, and Systems
A simulation based optimization algorithm for slack reduction and workforce scheduling
Proceedings of the 40th Conference on Winter Simulation
A prototype simulation tool for a framework for simulation-based optimization of assembly lines
Proceedings of the Winter Simulation Conference
Framework for simulation based scheduling of assembly lines
Proceedings of the Winter Simulation Conference
| Hi-index | 0.00 |
Our paper deals with the scheduling of complex assembly lines with a focus on Job Shop Scheduling Problems that exhibit several assembly specific characteristics: many isolated project networks with precedence constraints and thousands of jobs, time bound requirements for jobs and projects, limited resources with individual scheduling and resource lock rules. Formally it is defined as a Multi-Mode Resource-constrained Multi-Project Scheduling Problem with splitting activities. Problems that display these characteristics are often difficult to solve with classical scheduling approaches within acceptable runtime. Simulation-Based Optimization offers an auspicious manner of dealing with those domain specific problems. Using this approach we present a decentralized heuristic evident in self-organization in nature. Typical algorithms attempt to solve the above problems globally. In our solution, the jobs of the network take over the active role. They communicate with their neighbors and the allocated resources, each having the local goal to optimize their own situation.