Crew schedules on the South African Transport Services are done by roster compilers at depots. A method that uses heuristic and mathematical programming algorithms was developed to replace existing hand methods. It is a two stage method that will use a microcomputer to assist roster compilers to draw up crew schedules. Initially timetables are subdivided into shifts and then they are combined into crew schedules. The solution, which produces a significant improvement compared with an existing crew schedule and an existing method, has been accepted in principle and computer programming has begun. In Appendix E another heuristic for the scheduling of league matches is described.

by Kenneth Wing Chung Tang. / Thesis (M.Phil.)--Chinese University of Hong Kong, 1995. / Includes bibliographical references (leaves 64-65). / LIST OF TABLES --- p.vi / LIST OF FIGURES --- p.vii / Chapter 1. --- INTRODUCTION --- p.1 / Chapter 1.1 --- Staff Scheduling Overview --- p.2 / Chapter 1.1.1 --- Days-off scheduling --- p.7 / Chapter 1.1.2 --- Shift Scheduling --- p.8 / Chapter 1.1.3 --- Tour Scheduling --- p.9 / Chapter 1.2 --- Outline of The Work of The Thesis --- p.11 / Chapter 2. --- NETWORK MODEL FOR STAFF SCHEDULING --- p.13 / Chapter 2.1 --- The Basic Network Model --- p.13 / Chapter 2.1.1 --- General Idea --- p.13 / Chapter 2.1.2 --- Modeling Precedent Relationship Constraints by Arcs --- p.15 / Chapter 2.1.3 --- Modeling Shift Stretch Constraints by Nodes --- p.16 / Chapter 2.1.4 --- Modeling to Handle Side Constraints --- p.17 / Chapter 2.1.5 --- Mathematical Model --- p.21 / Chapter 2.2 --- Solving The Network Model With Side Constraints --- p.23 / Chapter 2.2.1 --- Basis Partitioning Network Simplex method --- p.23 / Chapter 2.2.2 --- A Two-Phase Heuristic for Schedules Construction --- p.29 / Chapter 3. --- APPLICA TION IN AN AIR CARGO TERMINAL --- p.55 / Chapter 3.1 --- Background And Problem Statement --- p.35 / Chapter 3.2 --- Generation of Staff Requirement Patterns --- p.38 / Chapter 3.3 --- A Typical Setting of Parameters --- p.41 / Chapter 3.4 --- Case One: Staff Requirement for Each Shift Is Fixed --- p.43 / Chapter 3.4.1 --- Conversion of hourly requirements to shift requirements --- p.43 / Chapter 3.4.2 --- Network Modeling --- p.44 / Chapter 3.4.3 --- An Example --- p.47 / Chapter 3.4.4 --- Computational result on different staff requirements --- p.49 / Chapter 3.5 --- Case Two: Staff Requirement for Each Shift Is Changing --- p.50 / Chapter 3.5.1 --- Network modeling --- p.51 / Chapter 3.5.2 --- An Example --- p.52 / Chapter 3.5.2.1 --- Overlapping shifts with one kind of break times --- p.54 / Chapter 3.5.2.2 --- Overlapping shifts with two kinds of break times --- p.56 / Chapter 3.5.2.3 --- Overtime work --- p.57 / Chapter 3.5.3 --- Computational results on different staff requirement patterns --- p.60 / Chapter 4. --- CONCLUSION --- p.62 / Chapter 5. --- BIBLIOGRAPHY --- p.64 / Chapter 6. --- APPENDIX --- p.66 / Chapter 6.1 --- Applying the heuristic to complete the incomplete schedules --- p.66 / Chapter 6.2 --- List of Schedules --- p.68 / Chapter 6.2.1 --- Terminologies --- p.68 / Chapter 6.2.2 --- The Optimal Schedules for Case One --- p.69 / Chapter 6.2.3 --- The Optimal Schedules for Case Two --- p.70 / Chapter 6.2.4 --- The Optimal Schedules with One-hour Break in One Shift --- p.71 / Chapter 6.2.5 --- The Optimal Schedules with Breaks after 4 and 3 Hours of Work --- p.72 / Chapter 6.2.6 --- The Optimal Schedules with Overtime Shifts --- p.73

by Wong Tin-Lam. / Thesis (M.Phil.)--Chinese University of Hong Kong, 1998. / Includes bibliographical references (leaves 70-73). / Abstract --- p.ii / Acknowledgement --- p.iii / Chapter 1 --- Introduction --- p.1 / Chapter 1.1 --- Scheduling Problems --- p.1 / Chapter 1.2 --- Literature Review --- p.4 / Chapter 1.2.1 --- Sized Multiprocessor Task Scheduling --- p.5 / Chapter 1.2.2 --- Fixed Multiprocessor Task Scheduling --- p.6 / Chapter 1.2.3 --- Set Multiprocessor Task Scheduling --- p.8 / Chapter 1.3 --- Organization of Thesis --- p.10 / Chapter 2 --- Overview --- p.11 / Chapter 2.1 --- Machine Environment --- p.11 / Chapter 2.2 --- The Jobs and Their Requirements --- p.12 / Chapter 2.3 --- Assumptions --- p.13 / Chapter 2.4 --- Constraints --- p.14 / Chapter 2.5 --- Objective --- p.15 / Chapter 2.6 --- An Illustrative Example --- p.17 / Chapter 2.7 --- NP-Hardness --- p.20 / Chapter 3 --- Methodology --- p.22 / Chapter 3.1 --- Dynamic Programming --- p.22 / Chapter 3.1.1 --- Problem Analysis --- p.24 / Chapter 3.2 --- Key Idea to solve the problem --- p.27 / Chapter 3.3 --- Algorithm --- p.28 / Chapter 3.3.1 --- Phase 1 --- p.28 / Chapter 3.3.2 --- Phase 2 --- p.37 / Chapter 4 --- Extensions --- p.46 / Chapter 4.1 --- "Polynomially Solvable Cases P2 --- p.46 / Chapter 4.1.1 --- Dynamic Programming --- p.47 / Chapter 4.2 --- "Set Problem P2/setj,prmp/TmaX" --- p.55 / Chapter 4.2.1 --- Processing times for set jobs --- p.56 / Chapter 4.2.2 --- Algorithm --- p.58 / Chapter 4.3 --- k´ؤMachine Problem with only two types of jobs --- p.64 / Chapter 5 --- Conclusion and Future Work --- p.67 / Chapter 5.1 --- Conclusion --- p.67 / Chapter 5.2 --- Some Future Work --- p.68 / Bibliography --- p.70

Yip Ka-yun. / Thesis (M.Phil.)--Chinese University of Hong Kong, 1998. / Includes bibliographical references (leaves 107-113). / Abstract also in Chinese. / Chapter Chapter 1 --- Introduction --- p.1 / Chapter 1.1 --- Overview --- p.1 / Chapter 1.2 --- Our Contributions --- p.2 / Chapter 1.3 --- Organization of the Thesis --- p.4 / Chapter Chapter 2 --- Literature Review --- p.5 / Chapter 2.1 --- Overview --- p.5 / Chapter 2.2 --- Research in Capacitated Lot Sizing Problem without significant setup times --- p.5 / Chapter 2.3 --- Research in Capacitated Lot Sizing Problem with setup time consideration --- p.12 / Chapter 2.4 --- Summary --- p.15 / Chapter Chapter 3 --- Capacitated Lot Sizing Problem with Setup Times --- p.16 / Chapter 3.1 --- Overview --- p.16 / Chapter 3.2 --- Problem Description and Formulation --- p.20 / Chapter 3.2.1 --- Our problem formulation / Chapter 3.2.2 --- Comparison between our problem formulation and traditional problem formulation / Chapter 3.3 --- Description of the Algorithm --- p.26 / Chapter 3.3.1 --- Wagner-Whitin algorithm / Chapter 3.3.2 --- Transportation problem / Chapter 3.3.3 --- Consistence test / Chapter 3.3.4 --- Subgradient optimization / Chapter 3.3.5 --- Computation of lower bound / Chapter 3.4 --- Design of Experiment --- p.43 / Chapter 3.4.1 --- Product demands / Chapter 3.4.2 --- Setup costs / Chapter 3.4.3 --- Setup times / Chapter 3.4.4 --- Capacity costs / Chapter 3.4.5 --- Inventory holding costs / Chapter 3.4.6 --- Quantity of capacity available for production / Chapter 3.4.7 --- Capacity absorption rate / Chapter 3.4.8 --- Generation of larger problems / Chapter 3.4.9 --- Initialization of Lagrangean multipliers / Chapter 3.4.10 --- Close test / Chapter 3.5 --- Open test --- p.58 / Chapter 3.6 --- Managerial Implications --- p.61 / Chapter 3.7 --- Summary --- p.61 / Chapter Chapter 4 --- Capacitated Lot Sizing Problem without Setup Times --- p.63 / Chapter 4.1 --- Overview --- p.63 / Chapter 4.2 --- Problem Description and Formulation --- p.64 / Chapter 4.3 --- Description of the Algorithm --- p.67 / Chapter 4.3.1 --- Decomposition scheme / Chapter 4.3.2 --- Wagner-Whitin algorithm / Chapter 4.3.3 --- Transportation problem / Chapter 4.3.4 --- Subgradient optimization / Chapter 4.3.5 --- Computation of lower bound / Chapter 4.4 --- Design of Experiment --- p.80 / Chapter 4.4.1 --- Product demands / Chapter 4.4.2 --- Setup costs / Chapter 4.4.3 --- Capacity costs / Chapter 4.4.4 --- Inventory holding costs / Chapter 4.4.5 --- Quantity of capacity available for production / Chapter 4.4.6 --- Capacity absorption rate / Chapter 4.4.7 --- Generation of larger problems / Chapter 4.4.8 --- Initialization of Lagrangean multipliers / Chapter 4.4.9 --- Selection of the extent of geometrical reduction and exponential smoothing / Chapter 4.4.10 --- Close test / Chapter 4.5 --- Open test --- p.92 / Chapter 4.6 --- Managerial Implications --- p.95 / Chapter 4.7 --- Comparison with other approaches --- p.96 / Chapter 4.7.1 --- Gilbert and Madan's approach / Chapter 4.7.2 --- Our algorithm for CLS problem with setup time consideration / Chapter 4.8 --- Summary --- p.102 / Chapter Chapter 5 --- Conclusion --- p.104 / Appendix A Vogel's approximation method --- p.106 / Bibliography --- p.107

Thesis. 1980. Ph.D.--Massachusetts Institute of Technology. Dept. of Electrical Engineering and Computer Science. / MICROFICHE COPY AVAILABLE IN ARCHIVES AND ENGINEERING. / Vita. / Bibliography: leaves 144-145. / Ph.D.

Thesis (B.S.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 1982. / MICROFICHE COPY AVAILABLE IN ARCHIVES AND ENGINEERING / Bibliography: leaf 54. / by Paul Alan Roush. / B.S.

by Lam Sze-sing. / "April 2000." / Thesis (Ph.D.)--Chinese University of Hong kong, 2000. / Includes bibliographical references 9p. 149-157). / Electronic reproduction. Hong Kong : Chinese University of Hong Kong, [2012] System requirements: Adobe Acrobat Reader. Available via World Wide Web. / Electronic reproduction. Ann Arbor, MI : ProQuest Information and Learning Company, [200-] System requirements: Adobe Acrobat Reader. Available via World Wide Web. / Mode of access: World Wide Web. / Abstracts in English and Chinese.

Thesis. 1978. M.S.--Massachusetts Institute of Technology. Dept. of Electrical Engineering and Computer Science. / MICROFICHE COPY AVAILABLE IN ARCHIVES AND ENGINEERING / Includes bibliographical references. / M.S.

Thesis. 1976. M.S.--Massachusetts Institute of Technology. Dept. of Civil Engineering. / Microfiche copy available in Archives and Engineering. / Bibliography: leaves 270-272. / M.S.

Abstract not available