Lau Chun Ming. / Thesis (M.Phil.)--Chinese University of Hong Kong, 1997. / Includes bibliographical references (leaves 122-125). / Chapter Chapter 1: --- Introduction --- p.1 / Chapter 1.1 --- Overview --- p.1 / Chapter 1.2 --- Static Plant Layout Problem --- p.1 / Chapter 1.3 --- Dynamic Plant Layout Problem --- p.3 / Chapter 1.4 --- Example Problem of SPLP --- p.4 / Chapter 1.5 --- Formulation of SPLP --- p.7 / Chapter 1.6 --- Example Problem of DPLP --- p.8 / Chapter 1.7 --- Mathematical Model of DPLP --- p.12 / Chapter 1.8 --- Characteristics of the DPLP --- p.13 / Chapter 1.9 --- Constrained Dynamic Plant Layout Problem (CDPLP) --- p.14 / Chapter 1.10 --- Mathematical Model of CDPLP --- p.14 / Chapter 1.11 --- Objective of the Research --- p.15 / Chapter 1.12 --- Conclusion --- p.16 / Chapter Chapter 2: --- Literature Review --- p.17 / Chapter 2.1 --- Overview --- p.17 / Chapter 2.2 --- Static Plant Layout Problem (SPLP) --- p.17 / Chapter 2.2.1 --- The optimal algorithms / Chapter 2.2.2 --- The sub-optimal algorithms / Chapter 2.2.3 --- Construction algorithms / Chapter 2.2.4 --- Improvement algorithms / Chapter 2.3 --- Dynamic Plant Layout Problem (DPLP) --- p.21 / Chapter 2.4 --- Conclusion: --- p.26 / Chapter Chapter 3: --- Genetic Algorithms in DPLP --- p.27 / Chapter 3.1 --- Introduction of Genetic Algorithms --- p.27 / Chapter 3.2 --- Genetic Algorithms in DPLP --- p.28 / Chapter 3.2.1 --- Encoding of a solution / Chapter 3.2.2 --- Fitness function / Chapter 3.2.3 --- Crossover operator / Chapter 3.2.4 --- Selection scheme / Chapter 3.2.5 --- Replacement and reproduction / Chapter 3.2.6 --- Mutation / Chapter 3.2.7 --- Initialization of parent pool / Chapter 3.2.8 --- Termination criterion / Chapter 3.3 --- Summary of the Proposed Method --- p.50 / Chapter Chapter 4: --- Computational Result of GA in DPLP --- p.51 / Chapter 4.1 --- Overview --- p.51 / Chapter 4.2 --- Characteristics of the Testing Problems --- p.51 / Chapter 4.3 --- Mathematical Model of DPLP for the Testing Problem --- p.52 / Chapter 4.4 --- The Design of Experiment --- p.53 / Chapter 4.4.1 --- The experiment / Chapter 4.4.2 --- Generating the initial layouts: / Chapter 4.5 --- Result: --- p.56 / Chapter 4.6 --- Analysis of Results --- p.60 / Chapter 4.6.1 --- 6department problems / Chapter 4.6.2 --- 15and 30 department problems / Chapter 4.7 --- Conclusion --- p.66 / Chapter Chapter 5: --- Constrained Dynamic Plant Layout Problem --- p.68 / Chapter 5.1 --- Overview --- p.68 / Chapter 5.2 --- The Mathematical Model of CDPLP --- p.69 / Chapter 5.3 --- Properties of CDPLP --- p.69 / Chapter 5.4 --- The Proposed GA on CDPLP --- p.71 / Chapter 5.4.1 --- Introduction / Chapter 5.4.2 --- Procedure / Chapter 5.4.3 --- Properties of dynamic programming under the dummy periods / Chapter 5.4.4 --- Properties of the proposed GA under the dummy periods / Chapter 5.4.5 --- The maximum number of iteration for the procedure / Chapter 5.5 --- Design of Experiment --- p.78 / Chapter 5.6 --- Result of Experiment on CDPLP --- p.81 / Chapter 5.7 --- Analysis of Results --- p.91 / Chapter 5.7.1 --- Type 1 budget (self): / Chapter 5.7.2 --- The average cost of the test / Chapter 5.8 --- Conclusion: --- p.93 / Chapter Chapter 6: --- Conclusion --- p.94 / Appendix A: The Improved Implementation for Conway and Venkataramanan's GA --- p.96 / Appendix B: Computational Result for CDPLP --- p.98 / Bibliography --- p.122

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Plant layout procedures available today consider either the quantitative attribute or the qualitative attribute of the layout problem. These procedures are based on maximizing or minimizing one objective function. Some of the procedures that address the multi-attribute nature of the plant layout problem are based on assigning weights to objective functions and then solving the problem by heuristic methods. Exact methods guarantee optimal solution but are computationally intensive for large sized problems. Heuristic methods do not guarantee optimal solution, but are computationally less intensive and relatively faster than the exact methods. This thesis suggests a procedure for solving the multi-attribute plant layout problem. The procedure is based on formulating the plant layout problem as a Quadratic Assignment Problem. Solution to the formulation is achieved by solving it by a combination of exact and heuristic methods. This solution procedure gives better results than just the heuristic method and is not computationally intensive. A computer implementation of the proposed procedure is developed in "C" programming language. A detailed experimentation is conducted to study the performance of the proposed procedure as compared to a well known procedure called Blocplan. The layouts generated by the proposed procedure are found to be much better than those generated by Blocplan. In the literature there is no discussion on the criticality of a layout to the change in flow related input data. An analysis is performed to study the affect of change in flow related input data on the final layout and a measure is developed for determining the criticality of a given layout to the change in flow related input data for the case of equal size departments. / M.S.