Algorithms
  • Introduction
  • Algorithms
    • Insertion Sort
    • Shell Sort
    • Selection Sort
    • Heap Sort
    • Merge Sort
    • Quick Sort
    • Dual Pivot QuickSort
    • Radix Exchange Sort
  • Data Structures
    • Basic Datastructures
      • Table or Array
      • List
      • Linked List
      • Stack
      • Queue
      • Deque
      • Dictionary
      • HashTables
    • Trees
      • Tree
      • Binary Search Tree
      • Heap
      • Red-Black Trees
      • Splay Trees
      • Randomized Search Trees
    • Dynamic Programming
      • Fibonacci
      • Knapsack
      • Optimal Binary Search Trees
      • Longest Common Sub sequence
    • External Data Structures
      • B-Trees
      • Variants
    • Multi-dimensional Data Structures
      • Point-Region Quadtree
      • Point-Quadtrees
    • Priority Queues
      • Binomial Queues
  • Graphs
    • Basics
    • Depth First Search
    • Applications of Depth First Search
    • Breadth First Search
    • Shortest Paths
    • Transitive Closure
    • Flow Networks
    • Matching
  • Strings
    • Data Structures for Strings
      • Tries
        • Binary Tries
        • Multiway Trie
        • Patricia Tries
      • Variable Length-code
        • Elias Code
        • Gamma Code
        • Fibonacci Code
      • Huffmancode
      • Ternary Search Tree
    • Searching in Strings
      • Prefix Function
      • Knuth-Morris-Pratt
      • Boyer-Moore
      • Monte-Carlo Algorithms
      • Karp-Rabin
      • Automatons
      • Shift-AND
    • Indexing Text
      • Suffix Trees
      • Suffix Arrays
      • Search Engines & Inverted Files
  • P and NP
    • Introduction
    • SAT and 3-SAT
    • Graph Problems
    • Problems with Collections
    • Networks
    • Data storage
  • Metaheuristics
    • Trajectory Methods
      • Local Search
      • Simulated Annealing
      • Tabu Search
    • Population Based
      • Ant Colony
      • Evolutionary Computation
  • Sources
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  1. Metaheuristics
  2. Trajectory Methods

Local Search

PreviousTrajectory MethodsNextSimulated Annealing

Last updated 6 years ago

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The local search metaheuristic is an iterative improvement heuristic, since every move is only applied if the result is better than the current solution. The algorithm stops as soon as it finds a local minimum.

Algorithm

  1. GenerateInitialSolution

  2. while(improvement possible)

    1. Improve the solution until no possible improvement is found

Example

The traveling salesman problem: A salesman has to go to N doors to sell his goods. What is the shortest path that he can take?

* Metaheuristics in Combinatorial Optimization: Overview and Conceptual Comparison