taop18: supply chain optimization - linköping...
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TAOP18: Supply Chain Optimization Nils-Hassan Quttineh Department of Mathematics Division of Optimization
TAOP18: Lecture 1 2
Overview§ Introductoryexample§ Courseinforma8on
• Contents,Aims,Webpage• Organiza8on,Schedule• Examina8on
§ Introduc8ontoSupplyChainManagement§ Projects§ Arecentresearchproject (if8mepermits)
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TAOP18: Lecture 1 13
Teacher§ Nils-HassanQuNneh,MAI
• LecturerinOp8miza8on
• Email:[email protected]
• Office:B-building(3rdfloor),room3A:589(corridorA,topfloor,betweenentrance23-25)
B-building
27 25 23 21
Here!
TAOP18: Lecture 1 14
Aimsofthecourse§ Thecourseaimstogivethestudentsanabilitytomodel
op8miza8onproblems,andaninsightinhowmathema8caltheorycanbeusedtoformulateandsolveprac8calproblems,withemphasisonapplica8onsinsupplychain,distribu8onandtransporta8onplanning.
§ Thecoursealsoaimstogiveadeeperknowledgeabout
combinatorialop8miza8on,i.e.op8miza8onproblemswithanunderlyinggraphstructure.
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TAOP18: Lecture 1 15
Coursecontent§ Op8miza8oninSupplyChainManagement
• Transporta8on&Rou8ngproblems (Vehiclerou8ng)• Scheduling&Sequencing (StaffScheduling)
§ Modeling• Mathema8calModeling• AMPL
§ Solu8onmethods• AMPL/CPLEX (Lagrangianrelaxa8on)• Heuris8cs (Localsearch,Tabusearch)• Columngenera8on
TAOP18: Lecture 1 16
Courseorganiza8on§ Lectures
• Introduc8onstoproblemareas,Solu8onmethods,Projects
§ Seminars• 2h–Illustra8onofmethods&problemsolving
§ Presenta8ons• Oralpresenta8ons
§ Laboratorywork• Scheduledtoguaranteecomputeraccessandincreasepossibilityofteacheravailability
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TAOP18: Lecture 1 17
Examina8on§ Examina8onthroughprojects
§ Solve3differentprojects• Mandatorytohandin3wricenreports• Chooseoneprojecttopresentorally
§ Groups• Preferably2studentsineach(1isok,butnotthree)• Listsavailableinthebreak
§ Coursegrade• Possiblegradesare:U,3,4,5
TAOP18: Lecture 1 18
Examina8on,cont’d§ Eachprojectreportisgivenupto40points
• 30pointsforcorrectanswersonspecificques8ons.• Upto10pointsforthegeneralstructureofthereport,presenta8onofresults,discussions,relevantreferences.
§ Coursegrade• Topassthecourse,youneedatleast15points/project• Ifyougetlessthan15points,itispossibletorespondtocomments,andhopefullyimproveresults.
§ Gradelimits.3:>50points.4:>70points.5:>90points
(Oralpresenta8onmayimprovegradesinborderlinecases)
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TAOP18: Lecture 1 19
Timeplan Version3
Page 1
Timeplan TAOP18: Supply Chain Optimization
v.44 31 oct – 4 nov v.45 7-11 nov v.46 14-18 nov v.47 21-25 nov
må ti on to fr må ti on to fr må ti on to fr må ti on to fr
Project 1 Project 1 (3-18 nov) P 1
Project 2 Project 2 (16 nov – 2 dec)
Lecture 1 2 3 4 5
Sem/Lab Se 1 L 1 Se 2 L 2
v.48 28 nov – 2 dec v.49 5-9 dec v.50 12-16 dec v.51 19-23 dec
må ti on to fr må ti on to fr må ti on to fr må ti on to fr
Project 3 Project 3 (30 nov – 16 dec) P 3 x x
Project 2 2 P 2 x x
Lecture 6 7 x x
Sem/Lab Se 3 L 3 x x
TAOP18: Lecture 1 20
Homepage§ Coursewebpage:
• hcp://courses.mai.liu.se/GU/TAOP18/
§ Lisam:• hcps://lisam.liu.se
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Introduction to Supply Chain Management
TAOP18: Lecture 1 22
(SupplyChain)Planningarena
From Stadtler, H., Kilger, C., Supply Chain Management and Advanced Planning: Concepts, Models, Software, and Case Studies ( 2007)
Purchasing Production Distribution Sales
Strategic Network Planning
Demand planning
Order fulfillment & ATP
Master Planning
Distribution planning
Transport planning
Production planning
Scheduling & Sequencing
Purchasing & Material Requirements
planning (MRP)
Strategic
Tactic
Operational
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TAOP18: Lecture 1 23
StrategicNetworkPlanning§ Wheretolocatethenodesofthenetwork
• Produc8onsites• Warehousing/Distribu8onsites
§ Minimizecost,subjectto• Suppliers,Markets,Compe8tors• Produc8oncosts• Transporta8oncosts• Legisla8on,Exchangerates,Taxes,Duty,Risks,…
Purchasing Production Distribution Sales
Strategic Network Planning
Demand planning
Order fulfillment & ATP
Master Planning
Distribution planning
Transport planning
Production planning
Scheduling & Sequencing
Purchasing & Material Requirements
planning (MRP)
TAOP18: Lecture 1 24
MasterPlanning§ Produc8onanddeliveryplans,e.g.
• SynchronizedMaterialFlowintheen8rechain• Aggregateddataforen8rechain:-Produc8on-Transport-Stock
• Inputtodetailedplanning• Bocleneckfocus• Balancedemand&supplymidtermhorizon-Whattoproduce,where&when
Purchasing Production Distribution Sales
Strategic Network Planning
Demand planning
Order fulfillment & ATP
Master Planning
Distribution planning
Transport planning
Production planning
Scheduling & Sequencing
Purchasing & Material Requirements
planning (MRP)
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TAOP18: Lecture 1 25
Produc8onplanning,Scheduling&Sequencing§ Produc8onplanning
• Exactlyhowmuchtoproduceofwhatandinwhich8mebucket-Givendemand,Capacity,…
§ Scheduling/Sequencing• Inwhichorderinwhichmachines-Withwhichpersonnel,…
• Exactlywhat8medoesproduc8onstart
Purchasing Production Distribution Sales
Strategic Network Planning
Demand planning
Order fulfillment & ATP
Master Planning
Distribution planning
Transport planning
Production planning
Scheduling & Sequencing
Purchasing & Material Requirements
planning (MRP)
TAOP18: Lecture 1 26
Distribu8on&Transportplanning§ Distribu8onplanning/Tac8calchoices
• Costforkeepingstock,vs.transport-Inventorymanagement
• Distribu8onalterna8ves• Fleetmanagement
§ Opera8onalplanning/Transportplanning• Vehiclechoice• Routeplanning• Vehicleloading
Purchasing Production Distribution Sales
Strategic Network Planning
Demand planning
Order fulfillment & ATP
Master Planning
Distribution planning
Transport planning
Production planning
Scheduling & Sequencing
Purchasing & Material Requirements
planning (MRP)
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TAOP18: Lecture 1 27
Logis8csvs.Supplychain§ Logis8cs
• Logis8csmanagementisthatpartofsupplychainmanagementthatplans,implements,andcontrolstheefficient,effec8veforwardandreverseflowandstorageofgoods,servicesandrelatedinforma8onbetweenthepointoforiginandthepointofconsump8oninordertomeetcustomers'requirements.
§ CouncilofSupplyChainManagementProfessionals(CSCMP)
TAOP18: Lecture 1 28
Logis8csvs.Supplychain§ SupplyChainManagement (CSCMP)
• Supplychainmanagementencompassestheplanningandmanagementofallac8vi8esinvolvedinsourcingandprocurement,conversion,andalllogis8csmanagementac8vi8es.Importantly,italsoincludescoordina8onandcollabora8onwithchannelpartners,whichcanbesuppliers,intermediaries,thirdpartyserviceproviders,andcustomers.
• Inessence,supplychainmanagementintegratessupplyanddemandmanagementwithinandacrosscompanies.
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TAOP18: Lecture 1 29
SupplyChainNetworkstructure
1 2
n
1
n
1 2
n
End
Cus
tom
ers
/ con
sum
ers
Cus
tom
ers
Tier
3 to
n
Customers Tier 2
Focal company
Raw
mat
eria
l Sup
plie
rs
Sup
plie
rs
Tier
3 to
n
1 2
n
1
n
1 2
n
1
Suppliers Tier 2
1
3
n
Suppliers Tier 1
2
1
2
3
n
Customers Tier 1
2
Managed process links Monitored process links Not-Managed process links Non-Member process links
TAOP18: Lecture 1 30
SupplyChainNetworkstructure
1 2
n
1
n
1 2
n
End
Cus
tom
ers
/ con
sum
ers
Cus
tom
ers
Tier
3 to
n
Customers Tier 2
Raw
mat
eria
l Sup
plie
rs
Sup
plie
rs
Tier
3 to
n
1 2
n
1
n
1 2
n
1
Suppliers Tier 2
1
3
n
Suppliers Tier 1
2
1
2
3
n
Customers Tier 1
2
Focal company
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TAOP18: Lecture 1 31
Legend,SCstructure
Typesofbusinessprocesslinks:
1.Managedprocesslinks2.Monitoredprocesslinks3.Non-memberprocesslinks4.Not-managedprocesslinks
TAOP18: Lecture 1 32
Typesofmethods
● Scenariochoice● Strategicdecisions● …
● Organiza8onaldecisions● Marketstrategy
■ Quan8ta8vemethods
● Sta8s8csBusinessIntelligenceIntegra8on
● Op8miza8on
● Discreteeventsimula8onTDDC28inNorrköping,inSwedish,though…
§ Qualita8vemethods,ex.
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Supply Chain Optimization and Modeling
TAOP18: Lecture 1 34
Op8miza8on§ Schedulingochtransporta8onproblemsareorendifficult
combinatorialop8miza8onproblems
§ Combinatorialproblemswithnetworkstructure
Combinatorial optimization deals with problems that can be formulated as integer programs but have an underlying combinatorial structure that tends itself to the development of special algorithms.
Victor Klee
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TAOP18: Lecture 1 35
TAOP18: Lecture 1 36
Simplifiedproblem
Op8miza8onmodel
Solu8on
Results
Defini8ons,simplifica8ons,assump8ons
Problemformula8on
Solu8onmethod
Verifica8on
Valida8on
Realcaseproblem
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TAOP18: Lecture 1 37
Op8miza8onasatoolforplanning§ Ifweknow,forsure,thatthecomputedop8mal
solu8onwillnotbeop8malwhenimplemented,whyuseop8miza8onmethods?
§ Whatalterna8vesarethere?
§ Whatisthelikelihoodthatapar8cularnon-op8malcomputedsolu8on,isop8malinprac8ce?
TAOP18: Lecture 1 38
Simplifica8on,SupplyChain
Factories Suppliers Distribution
Centers
Customers
Transportation
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TAOP18: Lecture 1 39
SupplyChain§ Produc8onand/orinventorystepswithflow§ Products§ Capacity
• Transports(trucks,boats)• Factories,machines,inventory
§ Productsmaychange• Rawmaterial–semi-manufacturedar8cles–products
§ Timeperiods
TAOP18: Lecture 1 40
Op8miza8onmodelsinsupplychain§ OrenLP-problemsfortransporta8ontogetherwith
integerrequirements
§ Integerflow(products)• Numberoftrucks,boats
§ Binaryvariables• Using/openingfactories(fixcost)
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TAOP18: Lecture 1 41
Mathema8calformula8on
§ Variables• Orenthelinksabovewithmanyindex
Forexamplefactories,products,8meperiods (Xijp,Yjkp)
• Afixcostgivesacorrespondingvariableo Forexampleopenafactory (Zj)
Xijp Yjkp
Z j
TAOP18: Lecture 1 42
Mathema8calformula8on
Capacity
balance Node 0
Inventory ,
Demand
Supply
1,
jKzx
jyx
tjwyxw
kdy
ibx
ji
ij
kjk
iij
jtk
ktjttj
jkjk
jiij
∀≤
∀=−
∀=−+
∀≥
∀≤
∑
∑∑
∑
∑
∑
−
§ Objec8vefunc8on• Acostorenimpliesvariables,whichareincludedintheobjec8vefunc8on
§ Constraints
• Mostcommon:
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TAOP18: Lecture 1 43
Solu8onmethods§ Smallerproblemscanorenbesolvebyastrict
mathema8calmodelformula8onandbyusingcommercialsorware,e.g.AMPL/CPLEX.
§ Largerproblemsbecomesverydifficultsincethenumberofvariables(andconstraints)isverylarge.
§ Columngenera8on● Master-problemisasetcoveringproblem● Shortestpath,minimumcostproblemsassub-problems
§ Tabusearch
TAOP18: Lecture 1 44
Solu8onmethods§ Lagrangianrelaxa8on
• LagrangerelaxthecomplicatedconstraintsGivessmaller(easier)sub-problems,forexampleminimumcostproblemsforeachproduct.
• Providesop8mis8cboundsGivesalowerbound(LBD)forminimiza8onproblems.
• Themul8plierscanbeusedtofindafeasiblesolu8onAfeasiblesolu8onprovidespessimis8cbounds(UBD)
§ Heuris8cs• Greedyheuris8cs• Heuris8csusingtheLagrangianmul8pliers,etc.
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Projects
TAOP18: Lecture 1 46
Introduc8ontotheProjects§ Problemsolving
1. Problemanalysis2. Modeling(Problemformula8on)3. Datacollec8on4. Methoddevelopment(Algorithmdevelopment)5. Solvingtheproblem6. Implementa8on
§ Theprojectassignmentsfocusondifferentaspectsinthesupplychain.
§ Focusonop8miza8onasatoolinlargescaleproblems.
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TAOP18: Lecture 1 47
Project1:Supplychainmodeling
Factories Suppliers Distribution
Centers
Customers
Transportation
TAOP18: Lecture 1 48
Project1:Supplychainmodeling§ Modelingassignment
• DevelopaMixedIntegerLinearProgramming(MILP)modelforthetransporta8onproblem
§ Modelingenvironment
• AMPLandCPLEX(GURUBI)
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TAOP18: Lecture 1 49
Project1:Supplychainmodeling§ Lectures:2,3
§ Projectdescrip8on: Acendlectures,seeLisamwebpage
§ Labora8on8me (Notcompulsory)• ComputerRoom,B-building,entrance21,2ndfloor,B-corridor• MondayNovember7th17-21
§ Wricenreport• FridayNovember18th
§ Oralpresenta8on (Onlyifyouchoosetopresentproject1)• 15minutespresenta8onand5minutesofques8ons• MondayNovember21st• MakeanappointmentonLisamusingtheDoodle-link
TAOP18: Lecture 1 50
Project2:Vehiclerou8ng§ VehicleRou8ngProblemwithmul8plevehiclesand
mul8pledepots
§ Metaheuris8capproach:• Generateanefficienttransporta8onscheduleusingTabusearch
§ Modelingenvironment• Matlab,VBA,Java,…
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TAOP18: Lecture 1 51
VehicleRou8ngPlanning(VRP)
Delieveraspecificquan8tyfromthedepottoanumberofcustomers,givenanumberoftruckswithaspecificcapacity
5
6
32
7
demand
5
7
TruckCapacity=12
Depot
Costumer
TAOP18: Lecture 1 52
Project2:Vehiclerou8ng§ Lectures:4,5
§ Projectdescrip8on: Acendlectures,seeLisamwebpage
§ Labora8on8me (Notcompulsory)• ComputerRoom,B-building,entrance21,2ndfloor,B-corridor• MondayNovember21st17-21
§ Wricenreport• FridayDecember2nd
§ Oralpresenta8on (Onlyifyouchoosetopresentproject2)• 15minutespresenta8onand5minutesofques8ons• MondayDecember5th• MakeanappointmentonLisamusingtheDoodle-link
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TAOP18: Lecture 1 53
Project3:Aircrewscheduling§ Problemdescrip8on
• Thetourofduty(ToD)problemo Givenisanumberoffightsthatmustbecovered.o Findanefficientcombina8onofflightswhereallflightsarecovered.
• Tourgenera8onorencons8tutesdifficultproblems,duetocomplicatedrulesandregula8onsthatmustbesa8sfied.
TAOP18: Lecture 1 54
Project3:Aircrewscheduling
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TAOP18: Lecture 1 55
§ Programmingassignment• Developacolumngenera8onprocedurethatiden8fiestheop8malroutesfortheairlinecrew
§ Modelingassignment• Developacolumngenera8onscheme,i.e.amasterproblemandasubproblem
• Solvetheproblemforgivendata
§ Modelingenvironment• AMPLandCPLEX(GUROBI)
Project3:Aircrewscheduling
TAOP18: Lecture 1 56
§ Lectures:6,7
§ Projectdescrip8on: Acendlectures,seeLisamwebpage
§ Labora8on8me (Notcompulsory)• ComputerRoom,B-building,entrance21,2ndfloor,B-corridor• MondayDecember5th17-21
§ Wricenreport• FridayDecember16th
§ Oralpresenta8on (Onlyifyouchoosetopresentproject3)• 15minutespresenta8onand5minutesofques8ons• MondayDecember19th• MakeanappointmentonLisamusingtheDoodle-link
Project3:Aircrewscheduling