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Short-term scheduling of an open-pit mine with multiple objectives
- Source :
- Engineering Optimization. 49:777-795
- Publication Year :
- 2016
- Publisher :
- Informa UK Limited, 2016.
-
Abstract
- This article presents a novel algorithm for the generation of multiple short-term production schedules for an open-pit mine, in which several objectives, of varying priority, characterize the quality of each solution. A short-term schedule selects regions of a mine site, known as ‘blocks’, to be extracted in each week of a planning horizon (typically spanning 13 weeks). Existing tools for constructing these schedules use greedy heuristics, with little optimization. To construct a single schedule in which infrastructure is sufficiently utilized, with production grades consistently close to a desired target, a planner must often run these heuristics many times, adjusting parameters after each iteration. A planner's intuition and experience can evaluate the relative quality and mineability of different schedules in a way that is difficult to automate. Of interest to a short-term planner is the generation of multiple schedules, extracting available ore and waste in varying sequences, which can then be manually compared. This article presents a tool in which multiple, diverse, short-term schedules are constructed, meeting a range of common objectives without the need for iterative parameter adjustment.
- Subjects :
- Schedule
Engineering
Mathematical optimization
021103 operations research
Control and Optimization
business.industry
Applied Mathematics
0211 other engineering and technologies
Scheduling (production processes)
Open-pit mining
Time horizon
02 engineering and technology
Management Science and Operations Research
Planner
Multi-objective optimization
Industrial and Manufacturing Engineering
Computer Science Applications
0202 electrical engineering, electronic engineering, information engineering
020201 artificial intelligence & image processing
Heuristics
business
computer
Integer programming
computer.programming_language
Subjects
Details
- ISSN :
- 10290273 and 0305215X
- Volume :
- 49
- Database :
- OpenAIRE
- Journal :
- Engineering Optimization
- Accession number :
- edsair.doi.dedup.....dce7953052a7953c01f542d59d64493e