Production planning : operations scheduling with applications in manufacturing and services Erwin Hans (T&M-OMST) BB-235, tel. 3523, Johann Hurink (TW-STOR) Faculty of Technology and Management University of Twente Enschede, The Netherlands

Literature Book:Operations Scheduling with applications in 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 discussed methods 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 problem maximize/minimize objective subject to constraints

zManufacturing, e.g.: yjob shop / flow shop scheduling yworkforce scheduling ytool scheduling zServices, e.g.: yHotel / airline reservation systems yHospitals (operating rooms) zTransportation and distribution, e.g.: yvehicle scheduling, and routing yrailways Application areas

zInformation processing and communications: yCPU’s, series and parallel computing ycall centers zTime-tabling, e.g.: ylecture planning at a University ysoccer competition yflight scheduling zWarehousing, e.g.: yAGV scheduling, and routing zMaintenance, e.g.: yscheduling maintenance of a fleet of ships Application areas (cont.)

Scheduling in manufacturing Due to increasing market competition, companies strive to: zshorten delivery times zincrease variety in end-products zshorten production lead times zincrease resource utilization zimprove quality, reduce WIP zprevent production disturbances (machine breakdowns) --> more products in less time!

Different types of manufacturing control zMake and assemble to stock zMake to stock, assemble to order zMake to order zEngineer to order

Scheduling in a manufacturing planning and control framework zLong range forecasting and sales planning zFacility and resources planning zDemand management, aggregate and workforce planning zOrder acceptance and resource group loading zShop floor scheduling, workforce scheduling

Relations with other management areas zProduct and process design zProcess planning zInventory management and materials planning zPurchasing and procurement management zWarehousing and physical distribution

Scheduling in services zWorkforce Scheduling in yCall Centers yHospitals yEmployment agencies ySchools, universities zReservation Systems in yAirlines yHotels yCar Rentals yTravel Agencies zPostal services

Our approach Scheduling problem Model Conclusions Problem formulation Solve with algorithms

Scheduling models zJob shop scheduling zProject scheduling zFlexible Assembly Systems zLot sizing and scheduling zWorkforce scheduling, staffing zInterval scheduling, reservation systems, timetabling

Scheduling algorithms General solution Techniques: zMathematical programming ylinear, non-linear, (mixed) integer programming zExact methods (enumeration) ybranch-and-bound ydynamic programming ycutting plane / column generation methods zLocal search methods, heuristics ysimulated annealing ytabu search yadaptive search yk-opt methods ygenetic algorithms yneural networks

Scheduling algorithms (cont.) zHeuristics ydispatching rules ycomposite dispatching rules ybeam-search zDecomposition Techniques yTemporal decomposition (rolling horizon approach) yMachine decomposition (Shifting Bottleneck) zHybrid Methods ycombined usage of scheduling methods

Important characteristics of optimization techniques zQuality of Solutions Obtained (How Close to Optimal?) zAmount of CPU-Time Needed (Real-Time on a PC?) zEase of Development and Implementation (How much time needed to code, test, adjust and modify) zImplementation costs (Are expensive LP-solvers required?)

Local Search Value Objective Function Dispatching Rules 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 schedulingoffline scheduling

zERP-SYSTEMS ySAP, Baan, JD Edwards, People Soft, Navision, MFG Pro zGENERAL OPTIMIZATION yIlog, Dash, MINTO, OSL (IBM), XPRESS-MP, OML, XA zGENERAL SCHEDULING yI2, Cybertec, AutoSimulation, IDS Professor Scheer, ORTEC zSCHEDULING OIL AND PROCESS INDUSTRIES yHaverly Systems, Chesapeake, Finity, ORTEC zSCHEDULING CONSUMER PRODUCTS yManugistics, Numetrix zSCHEDULING WORKFORCE IN CALL CENTERS yAIX, TCS, Siebel Commercial Packages

Decision Support Systems Important issues in design of DSS: zDatabase design and management zData collection (e.g. barcoding system) zModule Design and Interfacing zGUI Design (Gantt-charts, etc.) zDesign of link between GUI and algorithm library (data organization before transfer) zInternal Re-optimization zExternal Re-optimization

GUI’S should allow: zInteractive Optimization yFreezing Jobs and Re-optimizing yCreating New Schedules by Combining Different Parts from Different Schedules zCascading and Propagation Effects After a Change or Mutation by the User, the system: ydoes Feasibility Analysis ytakes care of Cascading and Propagation Effects, ydoes Internal Re-optimization

Graphics user interfaces for scheduling production processes zGantt Chart Interface zDispatch List Interface zTime Buckets (resource capacity loading) zThroughput Diagrams zTime tables

Important objectives to be displayed zDue Date Related yNumber of late jobs yMaximum lateness yAverage lateness, tardiness zProductivity and Inventory Related yTotal Setup Time yTotal Machine Idle Time yAverage Time Jobs Remain in System, WIP zResource usage yresource shortage