The development of genetic algorithms for the finite capacity scheduling of complex products, with multiple levels of product structure.
From MaRDI portal
Publication:1410335
DOI10.1016/S0377-2217(02)00645-8zbMath1045.90031MaRDI QIDQ1410335
Publication date: 14 October 2003
Published in: European Journal of Operational Research (Search for Journal in Brave)
Deterministic scheduling theory in operations research (90B35) Approximation methods and heuristics in mathematical programming (90C59)
Related Items (6)
A resource portfolio planning model using sampling-based stochastic programming and genetic algorithm ⋮ A resource portfolio model for equipment investment and allocation of semiconductor testing industry ⋮ A mixed integer programming model for advanced planning and scheduling (APS) ⋮ Extending capacity planning by positive lead times and optional overtime, earliness and tardiness for effective master production scheduling ⋮ Price negotiation for capacity sharing in a two-factory environment using genetic algorithm ⋮ Optimising resource portfolio planning for capital-intensive industries under process-technology progress
Uses Software
Cites Work
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Multiple and bicriteria scheduling: A literature survey
- A tabu search approach for the flow shop scheduling problem
- A genetic algorithm for the job shop problem
- Some new results on simulated annealing applied to the job shop scheduling problem
- Deterministic job-shop scheduling: Past, present and future
- A Dynamic Programming Approach to Sequencing Problems
- Job shop scheduling with a genetic algorithm and machine learning
- A Fast Taboo Search Algorithm for the Job Shop Problem
- Dispatching rules for scheduling in assembly jobshops - Part 1
- A Branch-Bound Solution to the General Scheduling Problem
This page was built for publication: The development of genetic algorithms for the finite capacity scheduling of complex products, with multiple levels of product structure.
