Lecture 1
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Transcript of Lecture 1
Production planning: operations scheduling
with applications in manufacturing and services
Erwin Hans (T&M-OMST)BB-235, tel. 3523,
Johann Hurink (TW-STOR)[email protected]
Faculty of Technology and Management
University of TwenteEnschede, The Netherlands
Literature
Book:Operations Scheduling with applicationsin manufacturing and services
Authors: M. Pinedo, X. Chao
Handouts, also downloadable from website
Exam
These methods must be learned entirely (one or two questions about these will be in the exam):• adaptive search• branch-and-bound, beam-search• shifting bottleneck
The idea (approach) and application of all other discussedmethods must be learned (i.e., no formulas)
One question will be asked about the software demonstration
Aside from the discussed chapters from the book, the handouts must be learned
Scheduling: definition
Allocation of jobs to scarce resources
the types of jobs and resources depend on the specific situation
Combinatorial optimization problemmaximize/minimize objectivesubject to constraints
Manufacturing, e.g.: job shop / flow shop scheduling workforce scheduling tool scheduling
Services, e.g.: Hotel / airline reservation systems Hospitals (operating rooms)
Transportation and distribution, e.g.: vehicle scheduling, and routing railways
Application areas
Information processing and communications: CPU’s, series and parallel computing call centers
Time-tabling, e.g.: lecture planning at a University soccer competition flight scheduling
Warehousing, e.g.: AGV scheduling, and routing
Maintenance, e.g.: scheduling maintenance of a fleet of ships
Application areas (cont.)
Scheduling in manufacturingDue to increasing market competition,
companies strive to:shorten delivery timesincrease variety in end-productsshorten production lead timesincrease resource utilizationimprove quality, reduce WIPprevent production disturbances
(machine breakdowns)--> more products in less time!
Different types of manufacturing control
Make and assemble to stockMake to stock, assemble to orderMake to orderEngineer to order
Scheduling in a manufacturing planning and control framework
Long range forecasting and sales planningFacility and resources planningDemand management, aggregate and
workforce planningOrder acceptance and resource group
loading
Shop floor scheduling, workforce scheduling
Relations with other management areas
Product and process designProcess planningInventory management and materials
planningPurchasing and procurement
managementWarehousing and physical distribution
Scheduling in servicesWorkforce Scheduling in
Call Centers Hospitals Employment agencies Schools, universities
Reservation Systems in Airlines Hotels Car Rentals Travel Agencies
Postal services
Our approach
Scheduling problem
Model
Conclusions
Problem formulation
Solve with algorithms
Scheduling models
Job shop schedulingProject schedulingFlexible Assembly SystemsLot sizing and schedulingWorkforce scheduling, staffingInterval scheduling, reservation
systems, timetabling
Scheduling algorithmsGeneral solution Techniques:Mathematical programming
linear, non-linear, (mixed) integer programmingExact methods (enumeration)
branch-and-bound dynamic programming cutting plane / column generation methods
Local search methods, heuristics simulated annealing tabu search adaptive search
k-opt methods genetic algorithms neural networks
Scheduling algorithms (cont.)Heuristics
dispatching rules composite dispatching rules beam-search
Decomposition Techniques Temporal decomposition (rolling horizon
approach) Machine decomposition (Shifting Bottleneck)
Hybrid Methods combined usage of scheduling methods
Important characteristics of optimization techniques
Quality of Solutions Obtained(How Close to Optimal?)
Amount of CPU-Time Needed(Real-Time on a PC?)
Ease of Development and Implementation(How much time needed to code, test, adjust and modify)
Implementation costs(Are expensive LP-solvers required?)
Local Search
ValueObjectiv
eFunctio
n
DispatchingRules
Beam Search Branch and Bound
CPU - Time
Consideration of software companies w.r.t. optimization techniques
Implementation costs(Are expensive LP-solvers required? Easy to implement?)
vs.
What solution quality does the customer require?(Is an immediate answer required, or are long calculations allowed? Does customer accept complex solutions?)
online scheduling offline scheduling
ERP-SYSTEMS SAP, Baan, JD Edwards, People Soft, Navision, MFG
Pro GENERAL OPTIMIZATION
Ilog, Dash, MINTO, OSL (IBM), XPRESS-MP, OML, XA GENERAL SCHEDULING
I2, Cybertec, AutoSimulation, IDS Professor Scheer, ORTEC
SCHEDULING OIL AND PROCESS INDUSTRIES Haverly Systems, Chesapeake, Finity, ORTEC
SCHEDULING CONSUMER PRODUCTS Manugistics, Numetrix
SCHEDULING WORKFORCE IN CALL CENTERS AIX, TCS, Siebel
Commercial Packages
Decision Support Systems
Important issues in design of DSS:Database design and managementData collection (e.g. barcoding system)Module Design and InterfacingGUI Design (Gantt-charts, etc.)Design of link between GUI and algorithm
library (data organization before transfer)Internal Re-optimizationExternal Re-optimization
GUI’S should allow:Interactive Optimization
Freezing Jobs and Re-optimizing Creating New Schedules by Combining
Different Parts from Different SchedulesCascading and Propagation Effects
After a Change or Mutation by the User, the system:
does Feasibility Analysis takes care of Cascading and Propagation
Effects, does Internal Re-optimization
Graphics user interfaces for scheduling production processes
Gantt Chart InterfaceDispatch List InterfaceTime Buckets (resource capacity loading)Throughput DiagramsTime tables
Important objectives to be displayed
Due Date Related Number of late jobs Maximum lateness Average lateness, tardiness
Productivity and Inventory Related Total Setup Time Total Machine Idle Time Average Time Jobs Remain in System, WIP
Resource usage resource shortage