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Part I Assembly Line Design Problems |
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3 | (4) |
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3 | (1) |
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3 | (2) |
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5 | (1) |
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6 | (1) |
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7 | (6) |
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7 | (1) |
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Why the Design is Difficult? |
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8 | (1) |
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Design and Search Approaches |
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8 | (1) |
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The Gap Between Theory and Practice |
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8 | (2) |
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9 | (1) |
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Multiple Objective Problem |
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9 | (1) |
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9 | (1) |
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9 | (1) |
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10 | (1) |
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About the Quality of a Design |
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10 | (1) |
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Assembly Line Design Evolution |
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10 | (3) |
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Assembly Line: History and Formulation |
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13 | (18) |
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13 | (1) |
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Evolution of Today's Manufacturing Issues |
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13 | (2) |
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13 | (1) |
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13 | (1) |
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14 | (1) |
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14 | (1) |
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14 | (1) |
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Computers in Manufacturing |
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15 | (1) |
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15 | (1) |
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16 | (3) |
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Assembly Line Balancing Problems |
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19 | (8) |
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19 | (1) |
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Variability of Tasks Process Time |
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20 | (1) |
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21 | (2) |
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23 | (2) |
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Assembly Line Design Problems |
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25 | (2) |
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Why is the Balancing Problem Hard to Solve? |
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27 | (4) |
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Part II Evolutionary Combinatorial Optimisation |
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Evolutionary Combinatorial Optimisation |
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31 | (8) |
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31 | (1) |
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31 | (1) |
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How Do Genetic Algorithms Work? |
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32 | (6) |
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33 | (1) |
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Initialisation of the Population |
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34 | (1) |
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35 | (1) |
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36 | (2) |
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38 | (1) |
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38 | (1) |
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38 | (1) |
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Multiple Objective Grouping Genetic Algorithm |
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39 | (20) |
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39 | (1) |
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Multiple Objective Optimisation |
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39 | (1) |
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40 | (4) |
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The Use of Aggregating Functions |
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41 | (1) |
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41 | (1) |
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42 | (1) |
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Preferences and Local Search Methods |
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42 | (1) |
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43 | (1) |
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Grouping Problems and the Grouping Genetic Algorithm |
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44 | (2) |
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44 | (1) |
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45 | (1) |
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46 | (1) |
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46 | (1) |
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Multiple Objective Grouping Genetic Algorithm |
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46 | (5) |
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47 | (1) |
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Individual Construction Algorithm |
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48 | (1) |
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Overall Architecture of the Evolutionary Method |
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48 | (1) |
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49 | (2) |
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51 | (8) |
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Part III Assembly Line Layout |
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Equal Piles for Assembly Line Balancing |
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59 | (18) |
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59 | (1) |
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59 | (3) |
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59 | (2) |
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61 | (1) |
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Equal Piles for Assembly Line Balancing |
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62 | (9) |
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Motivation and Inspiration From Nature |
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63 | (1) |
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64 | (1) |
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Customising the Grouping Genetic Algorithm to the Equal Piles Assembly Line Problem |
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64 | (5) |
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69 | (2) |
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Extension to Multi-product Assembly Line |
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71 | (6) |
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Multiple Objective Problem |
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71 | (1) |
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72 | (5) |
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The Resource Planning for Assembly Line |
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77 | (16) |
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77 | (1) |
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78 | (1) |
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Dealing with Real-world Hybrid Assembly Line Design |
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79 | (5) |
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79 | (1) |
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80 | (2) |
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82 | (1) |
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83 | (1) |
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Incompatibilities Among Several Types of Equipment |
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84 | (1) |
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84 | (1) |
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85 | (7) |
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Distributing Tasks Among Stations |
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85 | (1) |
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86 | (3) |
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89 | (1) |
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Dealing with a Multi-product Assembly Line |
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90 | (1) |
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Complying with Hard Constraints |
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91 | (1) |
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Application of the Method |
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92 | (1) |
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93 | (12) |
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93 | (1) |
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Multi-product Assembly Line |
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93 | (1) |
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94 | (1) |
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94 | (1) |
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95 | (1) |
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Ordering Genetic Algorithm |
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95 | (4) |
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95 | (2) |
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97 | (2) |
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Balance for Operation Concept |
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99 | (6) |
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Non-fixed Number of Stations |
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100 | (2) |
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102 | (3) |
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Part IV The Integrated Method |
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Evolving to Integrate Logical and Physical Layout of Assembly Lines |
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105 | (16) |
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105 | (1) |
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105 | (1) |
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106 | (1) |
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106 | (10) |
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Development of the Interactive Method |
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108 | (7) |
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115 | (1) |
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116 | (5) |
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Concurrent Approach to Design Assembly Lines |
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121 | (16) |
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121 | (1) |
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121 | (1) |
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122 | (2) |
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123 | (1) |
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124 | (1) |
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124 | (1) |
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124 | (13) |
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Assembly Line Balancing Application: Outboard Motor |
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125 | (3) |
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Resource Planning Application: Car Alternator |
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128 | (9) |
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A Real-world Example Optimised by the OptiLine Software |
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137 | (8) |
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Conclusions and Future Work |
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145 | (4) |
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145 | (1) |
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Tendencies and Orientations |
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145 | (1) |
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146 | (1) |
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146 | (1) |
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Validation and Output Analysis |
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146 | (1) |
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147 | (2) |
References |
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149 | (10) |
Index |
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159 | |