Note: Intro -- Preface -- Contents -- Editors and Contributors -- 1 Navigation, Routing and Nature-Inspired Optimization -- 1 Introduction -- 2 Navigation in Animals -- 3 Navigation, Routing and Optimization -- 3.1 Optimization -- 3.2 Travelling Salesman Problem -- 3.3 Routing Problems -- 4 Nature-Inspired Algorithms for Optimization -- 4.1 Deterministic or Stochastic -- 4.2 Genetic Algorithms -- 4.3 Ant Colony Optimization -- 4.4 Particle Swarm Optimization -- 4.5 Firefly Algorithm -- 4.6 Cuckoo Search -- 4.7 Bat Algorithm -- 4.8 Flower Pollination Algorithm -- 4.9 Other Algorithms -- 5 Algorithmic Characteristics -- 5.1 Characteristics -- 5.2 Discretization and Solution Representations -- 6 Conclusions -- References -- 2 Navigation and Navigation Algorithms -- 1 Navigation Introduction -- 1.1 Navigation Origin -- 1.2 Navigation Definition -- 2 Development of Navigation -- 2.1 Initial Germination Stage -- 2.2 Low-Speed Development Stage -- 2.3 Prosperity and Active Stage -- 2.4 Blooming Stage -- 3 Navigation Algorithms -- 3.1 Ecosystem Simulation Algorithm -- 3.2 Swarm Intelligence Algorithm -- 3.3 Evolutionary Algorithm -- 3.4 Artificial Intelligence Algorithm -- 4 Development Tendency of Navigation Algorithms -- 4.1 Development Status of Navigation Algorithms -- 4.2 Development Tendency of Navigation Algorithm -- 5 Application of Navigation Algorithm -- 5.1 Application of Aviation Navigation Algorithm -- 5.2 Application of Land Navigation Algorithm -- 5.3 Application of Sea Surface Navigation Algorithm -- 5.4 Application of Underwater Navigation Algorithm -- References -- 3 Is the Vehicle Routing Problem Dead? An Overview Through Bioinspired Perspective and a Prospect of Opportunities -- 1 Introduction -- 2 Problem Statement -- 3 Recent Advances in Vehicle Routing Problem -- 3.1 Vehicle Routing Problem and Genetic Algorithms. , 3.2 Vehicle Routing Problem and Tabu Search -- 3.3 Vehicle Routing Problem and Simulated Annealing -- 3.4 Vehicle Routing Problem and Particle Swarm Optimization -- 3.5 Vehicle Routing Problem and Artificial Bee Colony -- 3.6 Vehicle Routing Problem and Ant Colony Optimization -- 3.7 Vehicle Routing Problem and Cuckoo Search -- 3.8 Vehicle Routing Problem and Imperialist Competitive Algorithm -- 3.9 Vehicle Routing Problem and Bat Algorithm -- 3.10 Vehicle Routing Problem and Firefly Algorithm -- 3.11 Vehicle Routing Problem and Other Nature-Inspired Metaheuristics -- 4 Challenges and Research Opportunities -- 5 Conclusions -- References -- 4 Review of Tour Generation for Solving Traveling Salesman Problems -- 1 Introduction -- 2 Traveling Salesman Problem (TSP) -- 2.1 History -- 2.2 Definitions -- 2.3 Applications -- 3 Best Tour Generation -- 3.1 Tour Construction -- 3.2 Tour Improvement -- 4 TSP Solution Space -- 4.1 Search Space Model -- 4.2 Constraints -- 5 Search Methods -- 6 Example: Discrete Cuckoo Search -- 6.1 First Layer: Construct a Solution -- 6.2 Second Layer:Improving the Solution -- 6.3 Third Layer: Local Optimum Escaping Methods -- 6.4 Fourth Layer: Discrete Cuckoo Search -- 7 Conclusion -- References -- 5 Flow Shop Scheduling By Nature-Inspired Algorithms -- 1 Introduction -- 2 Problem Definition -- 3 Literature Review -- 3.1 Ant Colony Optimization (ACO) -- 3.2 African Wild Dog Algorithm -- 3.3 Artificial Bee Colony (ABC) -- 3.4 Bacterial Foraging Optimization Algorithm (BFOA) -- 3.5 Bat Algorithm (BA) -- 3.6 Cuckoo Search (CS) -- 3.7 Crow Search Algorithm (CSA) -- 3.8 Firefly Algorithm (FA) -- 3.9 Flower Pollination Algorithm (FPA) -- 3.10 Fruit Fly Optimization Algorithm (FFO) -- 3.11 Gray Wolf Optimization (GWO) Algorithm -- 3.12 Invasive Weed Optimization (IWO) Algorithm -- 3.13 Migrating Birds Optimization (MBO) Algorithm. , 3.14 Monkey Search Algorithm -- 3.15 Particle Swarm Optimization (PSO) -- 3.16 Rhinoceros Search Algorithm (RSA) -- 3.17 Sheep Flock Heredity Algorithm (SFHA) -- 3.18 Shuffled Frog Leaping Algorithm (SFLA) -- 3.19 Water Wave Optimization (WWO) Algorithm -- 3.20 Whale Optimization Algorithm (WOA) -- 4 Future Direction of Research -- 5 Conclusions -- References -- 6 Mobile Robot Path Planning Using a Flower Pollination Algorithm-Based Approach -- 1 Introduction -- 1.1 Multi-robot Path Planning Approach -- 1.2 Soft Computing-Based Approaches -- 1.3 Challenges in the Application of Artificial Intelligent Approaches -- 2 Flower Pollination Algorithm -- 2.1 Basic Principle -- 2.2 Proposed Approach for Robot Path Planning -- 3 Results and Discussions -- 4 Conclusions for the Book Chapter -- References -- 7 Smartphone Indoor Localization Using Bio-inspired Modeling -- 1 Introduction -- 2 Background -- 2.1 Indoor Localization with Smartphones -- 2.2 Bio-inspired Computing: An Overview -- 3 Literature Review -- 3.1 Localization Using Bio-inspired Techniques -- 3.2 Smartphone Indoor Navigation Using Bio-inspired Techniques -- 4 Indoor Localization Using Artificial Neural Networks -- 4.1 System Model -- 4.2 Research Goal -- 4.3 Radiomap Modeling Using Artificial Neural Networks -- 5 Experimental Evaluation -- 5.1 Datasets and Evaluation Metrics -- 5.2 Evaluation Results -- 6 Conclusions and Future Challenges -- References -- 8 A New Obstacle Avoidance Technique Based on the Directional Bat Algorithm for Path Planning and Navigation of Autonomous Overhead Traveling Cranes -- 1 Introduction -- 2 BA, dBA and Variants -- 2.1 The Standard Bat Algorithm -- 2.2 Recent Advance in Improving the Bat Algorithm -- 2.3 The Directional Bat Algorithm -- 3 The Proposed Strategy for OTC Autonomous Path Planning -- 4 Simulation, Results and Discussions -- 5 Conclusions. , Appendix -- References -- 9 Natural Heuristic Methods for Underwater Vehicle Path Planning -- 1 Path Planning of Underwater Vehicle -- 1.1 Path Planning -- 1.2 Objective Optimization -- 1.3 Main Processes -- 1.4 The Key to the Problems -- 2 Characteristics of Underwater Path Planning -- 2.1 Safe Navigation Factors -- 2.2 Hidden Navigation Factors -- 2.3 Marine Environmental Factors -- 3 Intelligent Path Planning Algorithm -- 3.1 Neural Network Method -- 3.2 Fuzzy Logic Method -- 3.3 Genetic Algorithm -- 3.4 Ant Colony Algorithm -- 4 Firefly Algorithm -- 4.1 Bionics Principle -- 4.2 Algorithm Description -- 4.3 Algorithm Flow -- 4.4 Performance Analysis -- 4.5 Algorithm Improvement -- 5 Route Planning Based on Firefly Algorithm -- 5.1 Environmental Modeling -- 5.2 Route Expression -- 5.3 Evaluation Function -- 5.4 Process Design -- 5.5 Simulation -- References.