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Robust and Reactive Project Scheduling: A review and classification of procedures Willy Herroelen Roel Leus.

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Presentation on theme: "Robust and Reactive Project Scheduling: A review and classification of procedures Willy Herroelen Roel Leus."— Presentation transcript:

1 Robust and Reactive Project Scheduling: A review and classification of procedures Willy Herroelen Roel Leus

2 OUTLINE Introduction Deterministic Baseline Scheduling Generating Predictive and Reactive Schedules Different approaches to multi-project scheduling Conclusions

3 Introduction Procedures that yields workable BASELINE SCHEDULES Deterministic Environment Complete Information

4 Introduction Procedures that yields workable BASELINE SCHEDULES Min/Max Regular/Nonregular Objectives Subject to Precedence Constraints Resource Constraints

5 Introduction time A B C D E F Identifies peak & low capacity requirement periods Baseline Schedules serves very important functions time Resource Consumption

6 Introduction Material Procurement Preventive Maintenance Committment to due dates Basis for planning External Activities

7 Introduction Enables – visibility of future – agreement among all parties producer clients suppliers subcontractors and etc.

8 Introduction Supplier A Supplier B Producer Supplier C Enables Just In Time material delivery

9 Introduction Baseline Schedule – Vital for cash flow projections – Measures the perfomance Managers, Shop floor personel

10 Introduction More or Less execution times Unavailable resources Late arrival of materials Modified Release and due dates New Activities During execution, project is subject to considerable uncertainty P R O J E C T

11 Introduction Recognition of uncertainty – Proactive baseline schedule Protected against disruptions Minimize the total weighted instability – Reactive scheduling Doesn’t directly consider the uncertainty during the generation of the initial schedule Revises or re-optimizes the schedule when unexpected events or disruptions occur – Predictive – Reactive scheduling Generation of a predictive schedule Re-optimize by rescheduling policies

12 Deterministic Baseline Scheduling Development of a workable schedule – Defines the scheduled start times – Satisfies; Precedence contstraints Resource constraints – Optimizes the scheduling objective; most often project duration

13 Deterministic Baseline Scheduling

14 Deterministic Baseline Scheduling time Minimum Duration Schedule with constant resource level

15 Deterministic Baseline Scheduling time Minimum Duration Schedule with constant resource level Critical Path

16 Deterministic Baseline Scheduling time Minimum Duration Schedule with constant resource level Critical Path

17 Deterministic Baseline Scheduling time Minimum Duration Schedule with constant resource level Critical Path

18 Deterministic Baseline Scheduling time Minimum Duration Schedule with constant resource level Critical Path … 16

19 Deterministic Baseline Scheduling time Optimal for deterministic setting

20 Deterministic Baseline Scheduling time Optimal for deterministic setting -Extremely vulnerable to uncertainty 3’

21 Deterministic Baseline Scheduling time Optimal for deterministic setting -Extremely vulnerable to uncertainty -True optimality can only be ascertained in real world

22 Deterministic Baseline Scheduling time Optimal for deterministic setting -Extremely vulnerable to uncertainty -True optimality can only be ascertained in real world -Has insufficient built-in slack or flexibility Not ROBUST

23 Deterministic Baseline Scheduling Lack of Robustness Lack of Stability Lack of Quality : Not Solution Robust : Not Quality Robust Flexibility

24 Generating Predictive and Reactive Project Schedules Dynamic Scheduling – No baseline schedule – Decide which activity to start as time evolves – Stochastic Project Scheduling Precedence and resource constraints Multi stage decision process Scheduling strategies – Minimize the expected project duration ??????

25 Generation of a Baseline Schedule No anticipation of variability Proactive (robust) baseline scheduling – CC/BM – Robust precednce feasible schedules Solution robust Quality robust – S&Q Robust with resource constraints Reactive Scheduling – Schedule Reapir – Rescheduling – Contingent scheduling – Activity Crashing – Sensitivity Analysis

26 Generation of a Baseline Schedule No anticipation of variability Proactive (robust) baseline scheduling – CC/BM – Robust precedence feasible schedules Solution robust Quality robust – S&Q Robust with resource constraints Reactive Scheduling – Schedule Reapir – Rescheduling – Contingent scheduling – Activity Crashing – Sensitivity Analysis

27 Generation of a Baseline Schedule No anticipation of variability Proactive (robust) baseline scheduling – CC/BM – Robust precednce feasible schedules Solution robust Quality robust – S&Q Robust with resource constraints Reactive Scheduling – Schedule Reapir – Rescheduling – Contingent scheduling – Activity Crashing – Sensitivity Analysis

28 Generation of a Baseline Schedule No anticipation of variability Proactive (robust) baseline scheduling – CC/BM – Robust precednce feasible schedules Solution robust Quality robust – S&Q Robust with resource constraints Reactive Scheduling – Schedule Reapir – Rescheduling – Contingent scheduling – Activity Crashing – Sensitivity Analysis

29 Critical Chain Scheduling/Buffer Management CC/BM – Direct application of the theory of constraints to project management Identify Exploit Subordinate Elevate Repeat

30 Critical Chain Scheduling/Buffer Management Builds a baseline schedule – Aggressive median or Average activity duration estimates – Activity due dates are eliminated – Multi tasking is avoided Aggressive Median

31 Critical Chain Scheduling/Buffer Management Create a precendence feasible schedule – Consider the precedence constraints – Schedule the activities at their latest start times – Resolve the resource conflicts by moving activities earlier in time Indentify the critical chain – Determines the overall duration of the project

32 Critical Chain Scheduling/Buffer Management Precedence Feasible Schedule ActivityPrecedenceDuration , 53 96, 84

33 Critical Chain Scheduling/Buffer Management PB

34 Critical Chain Scheduling/Buffer Management PB FB

35 Critical Chain Scheduling/Buffer Management PB FB

36 Critical Chain Scheduling/Buffer Management PB FB RB

37 Critical Chain Scheduling/Buffer Management

38 PB FB RB Buffered Schedule

39 Critical Chain Scheduling/Buffer Management

40 Critical Chain Scheduling/Buffer Management

41 Critical Chain Scheduling/Buffer Management Projected Schedule

42 Critical Chain Scheduling/Buffer Management Conclusion after 110 Patterson test problem; – Updating the baseline schedule and critical chain at each decision point Best estimate of final project duration Yields smallest project duration – %50 buffer sizing, seriously overestimates – Using root-square-error method for buffer sizing is more beneficial as the problem size increases – Do not keep the critical chain activities in series – Recompute the baseline schedule at each decision point

43 Critical Chain Scheduling/Buffer Management In a multi-project environment 1.Prioritize the organization’s projects Avoid multi tasking 2.Plan the individual projects according to CC/BM Identify the bottleneck resource 3.Stagger the projects 4.Insert drum buffers 5.Measure and report the buffers 6.Manage the buffers

44 Generation of a Baseline Schedule No anticipation of variability Proactive (robust) baseline scheduling – CC/BM – Robust precedence feasible schedules Solution robust Quality robust – S&Q Robust with resource constraints Reactive Scheduling – Schedule Reapir – Rescheduling – Contingent scheduling – Activity Crashing – Sensitivity Analysis

45 Robust Precedence Feasible Schedules Solution Robust Schedules – Activity start times are insensitive to disruptions – Stable Quality Robust Schedules – Overall project duration is insensitive to disruptions – Robustnes in the objective function value

46 Solution Robust Schedules Mathematical Programming Model Stable Baseline Schedules Assumptions Resource can be booked in advanvence Single activity disruption Herroelen & Leus (2003)

47 Deadline = 14 Equal disruption probability P(duration of disruption=1) = 0,5 P(duration of disruption=2) = 0,5 9 Solution Robust Schedules Solution Robust Weighted Expected Deviation is minimized

48 Solution Robust Schedules

49 Solution Robust Schedules Stable Schedules, spread out the activities

50 Solution Robust Schedules 0,04 0,035 0,03 0,025 0,020 0,015 0,01 0,005 Solution Robust CC/BM (proj) Density Function of the Makespan Resource Constraints are disregarded Activity durations are stochastic (triangular) Min =10, Max =22 STABLE has HIGHER MAKESPAN

51 Solution Robust Schedules

52 Other types of schedule disruptions – less execution times – change in the execution mode planned / unplanned pre-emption – delay in the starting times – modification of the structure of the project new activities changed precedence Other metrics for stability measure – # of disrupted activities – # of re-planned activities

53 Quality Robust Schedules

54 Generation of a Baseline Schedule No anticipation of variability Proactive (robust) baseline scheduling – CC/BM – Robust precedence feasible schedules Solution robust Quality robust – S&Q Robust with resource constraints Reactive Scheduling – Schedule Reapir – Rescheduling – Contingent scheduling – Activity Crashing – Sensitivity Analysis

55 Solution and Quality Robust Schedules Precedence and Resource feasible

56 Solution and Quality Robust Schedules CC/BM Projected Schedule Solution and Quality Robust Schedule

57 Solution and Quality Robust Schedules Resource Allocation is the cruical issue that remains to be solved

58 Generation of a Baseline Schedule No anticipation of variability Proactive (robust) baseline scheduling – CC/BM – Robust precedence feasible schedules Solution robust Quality robust – S&Q Robust with resource constraints Reactive Scheduling – Schedule Reapir – Rescheduling – Contingent scheduling – Activity Crashing – Sensitivity Analysis

59 Reactive Scheduling Schedule modifications, made during execution May be based on various underlying strategies – Very simple techniques (schedule repair) – Full scheduling

60 Generation of a Baseline Schedule No anticipation of variability Proactive (robust) baseline scheduling – CC/BM – Robust precedence feasible schedules Solution robust Quality robust – S&Q Robust with resource constraints Reactive Scheduling – Schedule Reapir – Rescheduling – Contingent scheduling – Activity Crashing – Sensitivity Analysis

61 Generation of a Baseline Schedule No anticipation of variability Proactive (robust) baseline scheduling – CC/BM – Robust precedence feasible schedules Solution robust Quality robust – S&Q Robust with resource constraints Reactive Scheduling – Schedule Reapir – Rescheduling – Contingent scheduling – Activity Crashing – Sensitivity Analysis

62 Rescheduling Yang (1996) – New makespan minimization Artigues and Roubelat (2000) – Multi-project, Multi-mode – Ready times and due dates – Insert a new unexpected activity – Minimize the maximum lateness – They used a polynomial algorithm and tested in on 110 Patterson test problems against complete rescheduling – Insertion method outperforms complete recheduling – Mean increase of makespan ≤ inserted activity duration

63 Rescheduling Frequent Rescheduling – Instability and lack of continuity – Increased costs – Increased shop floor nervousness Minimum perturbation strategy – Minimize the start time differences – Minimize the number of activites that will be performed with different resources Using Match-up point – Match up with the pre-schedule at a certain time in future

64 Generation of a Baseline Schedule No anticipation of variability Proactive (robust) baseline scheduling – CC/BM – Robust precedence feasible schedules Solution robust Quality robust – S&Q Robust with resource constraints Reactive Scheduling – Schedule Reapir – Rescheduling – Contingent scheduling – Activity Crashing – Sensitivity Analysis

65 Contingent Scheduling Manual changes during execution Billaut and Roubelat (1996a,b) – Generate for every resoure a group sequence – Consider arbitrary ordering of operation inside each group. – If disruption occurs, switch from one solution to another Several other extensions are studied

66 Generation of a Baseline Schedule No anticipation of variability Proactive (robust) baseline scheduling – CC/BM – Robust precedence feasible schedules Solution robust Quality robust – S&Q Robust with resource constraints Reactive Scheduling – Schedule Reapir – Rescheduling – Contingent scheduling – Activity Crashing – Sensitivity Analysis

67 Sensitivity Analysis Hall and Posner (2000a, b) – Limits of parameters in which solution remains optimal – New optimal cost and solution after a parameter change

68 Sensitivity Analysis

69 Multi-project Scheduling Problem No single best method Best way for – Coordination and Scheduling of resources – Control of schedule, depends on the project environment Two key determinants 1.Variability 2.Independence

70 Multi-project Scheduling Problem what Estimates duration Process whenhow Project Parameters costqualitytime content Uncertainty & Variability Uncertainty & Variability ObjectivesPriorities Fundamental Relationships whom Trade off

71 Multi-project Scheduling Problem Ward and Chapman (2002) – Explore and Understand the origins of the uncertainties – Before managing them

72 Multi-project Scheduling Problem Hendricks et al.(2002) – Project Scatter Factor : degree of shared resources – Dependence ~ degree of free dispatching or scheduling – Intermediate milestones increases dependence – Uncertain or tight ready days increases dependence – All activities = Drum Activities + Remainder Project Non-Project Parties INTERNAL EXTERNAL

73 Multi-project Scheduling Problem TOTALLY DEPENDENT variability LOW HIGH RATHER DEPENDENT RATHER INDEPENDENT TOTALLY INDEPENDENT

74 Multi-project Scheduling Problem TOTALLY DEPENDENT variability LOW HIGH RATHER DEPENDENT RATHER INDEPENDENT TOTALLY INDEPENDENT No outside restrictions Deterministic schedule Minor Disruptions Uncertainty during execution Dispatching rules or predictive reactive scheduling Feasible schedule for drum activities Remainder activities are planned around them Drum Plan must be Robust Dispatching / predictive- reactive for remainder Shared resources Constrained activities Robust plan Aggregate plan Resource allocation with minimal conflicts Slacks if possible Robust Drum Plan Sufficient oppurtunity for uncertain events Resources are often workstations Rough ballpark plan for intermediate milestones

75 Multi-project Scheduling Problem TOTALLY DEPENDENT variability LOW HIGH RATHER DEPENDENT RATHER INDEPENDENT TOTALLY INDEPENDENT

76 Multi-project Scheduling Problem TOTALLY DEPENDENT variability LOW HIGH RATHER DEPENDENT RATHER INDEPENDENT TOTALLY INDEPENDENT Fire fighting mode beacuse of intermediate milestones

77 Multi-project Scheduling Problem TOTALLY DEPENDENT variability LOW HIGH RATHER DEPENDENT RATHER INDEPENDENT TOTALLY INDEPENDENT

78 Multi-project Scheduling Problem The role of CC/BM – Integrated methodology for project planning and execution – Needs to be credited for duration estimation problem Parkinson’s law and Student syndrome Multi tasking – Suitable for single projects

79 Summary and Conclusions Objective of the paper – Review the methodologies for proactive and reactive project scheduling – Proper scheduling methodology for different environments Generating S&Q robust with effective reactive scheduling mechanism are still burn-in CC/BM – Attracted a lot of attention – Suffers from Over simplification Not universally applicable

80 Thank you. Questions ?


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