Scheduling with controllable processing times and compression costs using population-based heuristics

DOI10.1080/00207540903433874zbMath1210.90093OpenAlexW1966241679MaRDI QIDQ3168916

Andreas C. Nearchou

Publication date: 27 April 2011

Published in: International Journal of Production Research (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/00207540903433874

zbMATH Keywords

schedulingmeta-heuristicsswarm intelligenceevolution strategiesdifferential evolutioncontrollable processing timesgenetic and evolutionary algorithmscrash costs

Mathematics Subject Classification ID

Deterministic scheduling theory in operations research (90B35) Approximation methods and heuristics in mathematical programming (90C59) Problem solving in the context of artificial intelligence (heuristics, search strategies, etc.) (68T20)

Related Items (1)

Controllable processing times in project and production management: analysing the trade-off between processing times and the amount of resources

Cites Work

• Unnamed Item
• Unnamed Item
• Recent approaches to global optimization problems through particle Swarm optimization
• A survey of results for sequencing problems with controllable processing times
• A bicriterion approach to time/cost trade-offs in sequencing
• Scheduling jobs on a single machine with release dates, delivery times and controllable processing times: Worst-case analysis
• Single-machine sequencing with controllable processing times
• Single machine scheduling with controllable processing times and compression costs. I: Equal times and costs
• Single machine scheduling with controllable processing times and compression costs. II: Heuristics for the general case
• Two parallel machine sequencing problems involving controllable job processing times
• Differential evolution -- a simple and efficient heuristic for global optimization over continuous spaces
• Some comments on sequencing with controllable processing times
• Single machine scheduling to minimize total compression plus weighted flow cost is NP-hard.
• A survey of scheduling with controllable processing times
• Multicriteria scheduling
• Choosing the Job Sequence and Processing Times to Minimize Total Processing Plus Flow Cost on a Single Machine
• Technical Note—Single Machine Scheduling with Controllable Processing Times and Number of Jobs Tardy
• Introduction to evolutionary computing

This page was built for publication: Scheduling with controllable processing times and compression costs using population-based heuristics