Cultural Algorithms. Robert G. Reynolds

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СКАЧАТЬ search for the Pareto Front....Figure 8.9 Full Week, Pareto Frontier with all Three Phases.Figure 8.10 No Sundays, Pareto Frontier, with all three Phases.Figure 8.11 Mon_Tue_Wed, Pareto Frontier with all three Phases.Figure 8.12 Thur_Fri_Sat Pareto Frontier with all three Phases.Figure 8.13 Curve fitting for Payout, Effort using No Sundays in Phase I.Figure 8.14 Curve fitting using for first half of the week, Phase II.Figure 8.15 Curve fitting using for second half of the week, Phase II.Figure 8.16 F Distribution showing Acceptance and Rejection Regions.

      9 Chapter 9Figure 9.1 Cultural Algorithm Schema [6].Figure 9.2 CAPSO's Pareto Front for CONSTR.Figure 9.3 CONSTR Parameters Corresponding to the Pareto Front.Figure 9.4 CONSTR Learning Curves.Figure 9.5 Proportion of each Knowledge Source within Weighted Roulette Whee...Figure 9.6 CONSTR: Number of Threads Per Run (Topographic Knowledge Source P...Figure 9.7 CAPSO's Pareto Front for SRN.Figure 9.8 SRN Parameter Values Corresponding to Pareto Front.Figure 9.9 SRN Learning Curves.Figure 9.10 SRN Knowledge Source Dominance.Figure 9.11 SRN Threads Per Run (Topographic Knowledge Progress).Figure 9.12 TNK Ideal Pareto Front.Figure 9.13 TNK Pareto Front.Figure 9.14 TNK Search Space.Figure 9.15 TNK Learning Curves.Figure 9.16 TNK Knowledge Source Dominance.Figure 9.17 TNK Number of Threads Per Run (Topographic Knowledge Source Prog...Figure 9.18 KITA Pareto Front.Figure 9.19 KITA Parameter Values.Figure 9.20 KITA Knowledge Source Scores.Figure 9.21 KITA Knowledge Source Dominance.Figure 9.22 KITA Threads Per Run (Topographic Knowledge Progress).Figure 9.23 KITA Feasible Region. (a) Feasible Region in the Decision Variab...

      10 Chapter 10Figure 10.1 An Underwater Archaeological Site.Figure 10.2 Dr. John O'Shea Pictured with an Ancient Artifact.Figure 10.3 A Component‐Level Diagram of the Land Bridge Program.Figure 10.4 The Low‐Scale Top‐Level Scan of the Land Bridge Data with 16 Reg...Figure 10.5 An Example of the Scaling Sampling.Figure 10.6 The Topography Map.Figure 10.7 The Topography Map with Water Elements.Figure 10.8 An Example of Calculating Vectors.Figure 10.9 The Flow Direction Data Represented on a Map.Figure 10.10 A Visualization of the Water Object Data.Figure 10.11 A Visualization of the Vegetation Data.Figure 10.12 An Image from James Fogarty's Program.Figure 10.13 An Example of the A* Spaced Goals.Figure 10.14 An Example of the Temporal Difference in the Hotspot Finder.Figure 10.15 The Output of Samuel Dustin Stanley's Hotspot Finder.Figure 10.16 Area 1 with Superimposed Artifact Markers.Figure 10.17 A More Recent Run of the Hotspot Finder.Figure 10.18 A Visual of the Investigated Area.Figure 10.19 A Visualization of the Cultural Algorithm.Figure 10.20 The Alpena–Amberley Land Bridge Broken into Large Sections.Figure 10.21 A Collection of Possible Formations.Figure 10.22 A Diagram of the Flow of Data, Starting with the Hierarchical P...Figure 10.23 A Side‐by‐Side Display of a Single Area Viewed in Two Timescape...Figure 10.24 The Regional Sections of the Alpena–Amberley Land Bridge.Figure 10.25 The Land Bridge System on Microsoft's XNA.Figure 10.26 The Land Bridge System on Unity.Figure 10.27 A Full A* Path from Alpena to Amberley, through 14 Regions.Figure 10.28 Comparative Pseudocode of A* and A*mbush Algorithms.Figure 10.29 Image of Three Consecutive A*mbush Herds.Figure 10.30 Natural Caribou Migration Pathways as seen from Above.Figure 10.31 Dendriform A*mbush Pseudocode.Figure 10.32 An Example Dendriform A*mbush Run.Figure 10.33 An Example of a Heavily Effort Weighted Path.Figure 10.34 Three Examples of Risk.Figure 10.35 An Example of a Heavily Nutrition Weighted Path.Figure 10.36 The ERN Permutation Run Boundaries for Spring and Fall.

      Guide

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      2 Table of Contents

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