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Full Description
This textbook provides a range of tools for optimization in the mineral industry, including examples with mathematical programming. Topics covered include a survey of the application of optimisation technologies; a review of optimisation algorithms with math programming, math modelling and an introduction to AMPL (a widely used math modelling language), applications of linear programming to business improvement studies, surface mining applications, underground mining applications and options analysis. The math programming and AMPL is supported by the www.ampl.coma and by the author's site, www.minesmith.com.au. This volume is intended for course use and was developed for 3rd and 4th year university education in mine planning and design or mine optimisation. Engineers, planners and policy makers in the minerals industry may find it beneficial for their professional activities as well.
Contents
Preface; Origin of book; Objectives of author; Outline of text; Use as an undergraduate and introductory graduate level textbook; Guidance for professional development; AcknowledgementsIntroductionOverview of mine planning and designLevels of responsibility and decision making Role of optimisation in mine planningMine planning process flowInfluence of General Mine Planning packagesOptimisation as practiced in the general industryOptimisation as a foundation for planning and designOverview of Optimisation TechnologyWhy Mathematical Programming?Linear ProgrammingInteger Programming and Combinatorial OptimizationSolution Algorithms for Linear and Mixed Integer ProgrammingProof of optimalityReview of alternative optimisation methodsContrast and comparison of technologies in their use and applicationSurvey of the application of optimisation in the minerals industryHistory of development of optimisation in mine planning and designLerchs-Grossman and pit optimisationLinear and Mixed Integer Programming as applied to pit scheduling with extensions to Lagrange ParameterizationWhittle and the development of nested pit methodologiesSurvey of research developmentSurvey of commercial applications of optimisation to mine planningGaps analysis and future trendsIntroduction to mine modeling and optimisation using AMPLStructure of a mathematical modelIntroduction to AMPLFormulating a Linear ProgramNetwork applicationsInteger and network programmingSolversAMPL/Solver interactionAdditional learning resources for math modelingPit Optimisation and Pushback generationFormulation and solution as a GraphSolution using LGFormulation of the ultimate pit problem as an LPSolution as a LP and unimodularityGenerating nested pitsSelecting pushbacksReview of commercial applicationsOpen Cut Production SchedulingScheduling using math programmingScheduling heuristics as applied to benches within mining stagesHeuristic approaches to finding a "good" scheduleFormulation as a MIPMIP solution strategies and schedule granularityMIP extensions to more complex problemsSequencing and scheduling of blast mastersBlending, throughput and feed limitationsFixed costs and capital expansion problemsStockpile optimisation and the cutoff problemUnderground Mine PlanningThe process of underground mine planningUsing simulated annealing to define a mining inventorySteiner Trees and access optimisationFormulation of the underground scheduling problem as a LPThe underground cutoff problem and overall strategy optimisationConverting a mining inventory into a reserveProduction versus activity scheduling and project managementOther Applications and ConsiderationsStrategic, tactical and operational mine planningHills of Value and option analysis using LP/MIPBusiness-wide planningOptimising multiple business unitsEquipment fleet and haulage optimisationExtensions to coal miningConclusionsTowards a discipline of mine planningGaps in the technologyGaps in the professionWhere to from here?Appendices* Additional website resources* Further readings in optimisation technology* A guide to applying AMPL to the minerals industry
