Algorithm

Q learning (model free value iteration) algorithm for deterministic cleaning robot in matlab

The following Matlab project contains the source code and Matlab examples used for q learning (model free value iteration) algorithm for deterministic cleaning robot. Q-learning with epsilon-greedy exploration Algorithm for Deterministic Cleaning Robot V1 The deterministic cleaning-robot MDP a cleaning robot has to collect a used can also has to recharge its batteries.

Fixed endpoints open multiple traveling salesmen problem genetic algorithm in matlab

The following Matlab project contains the source code and Matlab examples used for fixed endpoints open multiple traveling salesmen problem genetic algorithm. MTSPOF_GA Fixed Open Multiple Traveling Salesmen Problem (M-TSP) Genetic Algorithm (GA)   Finds a (near) optimal solution to a variation of the "open" M-TSP by   setting up a GA to search for the shortest route (least distance needed   for each salesman to travel from the start location to unique   individual cities and finally to the end location) Summary: 1.

A new optimization algorithm inspired by the states of matter in matlab

The following Matlab project contains the source code and Matlab examples used for a new optimization algorithm inspired by the states of matter . The ability of an Evolutionary Algorithm (EA) to find a global optimal solution depends on its capacity to find a good rate between exploitation of found so far elements and exploration of the search space.

Five elements algorithm in matlab

The following Matlab project contains the source code and Matlab examples used for five elements algorithm. The harmony elements algorithm is proposed as a global searching technique of numerical computing which inspired by the old Chinese philosophy: Doctrine of Wu Xing, the five color theorem, and the Hoffman-Singleton graph.

Genetic Algorithm Matlab Code

Genetic algorithm (GA) is a search heuristic that mimics the process of natural selection. This heuristic (also sometimes called a metaheuristic) is routinely used to generate useful solutions to optimization and search problems.[1] Genetic algorithms belong to the larger class of evolutionary algorithms (EA), which generate solutions to optimization problems using techniques inspired by natural evolution, such as inheritance, mutation, selection, and crossover.

genetic algorithm

Fixed start end point multiple traveling salesmen problem genetic algorithm in matlab

The following Matlab project contains the source code and Matlab examples used for fixed start end point multiple traveling salesmen problem genetic algorithm. MTSPF_GA Fixed Multiple Traveling Salesmen Problem (M-TSP) Genetic Algorithm (GA)   Finds a (near) optimal solution to a variation of the M-TSP by setting   up a GA to search for the shortest route (least distance needed for   each salesman to travel from the start location to individual cities   and back to the original starting place) Summary: 1.

Fixed start open multiple traveling salesmen problem genetic algorithm in matlab

The following Matlab project contains the source code and Matlab examples used for fixed start open multiple traveling salesmen problem genetic algorithm. MTSPOFS_GA Fixed Start Open Multiple Traveling Salesmen Problem (M-TSP) Genetic Algorithm (GA)   Finds a (near) optimal solution to a variation of the "open" M-TSP by   setting up a GA to search for the shortest route (least distance needed   for each salesman to travel from the start location to unique individual   cities without returning to the starting location) Summary: 1.

Fixed start open traveling salesman problem genetic algorithm in matlab

The following Matlab project contains the source code and Matlab examples used for fixed start open traveling salesman problem genetic algorithm. TSPOFS_GA Fixed Start Open Traveling Salesman Problem (TSP) Genetic Algorithm (GA)   Finds a (near) optimal solution to a variation of the TSP by setting up   a GA to search for the shortest route (least distance for the salesman   to travel from a FIXED START to the other cities exactly once without   returning to the starting city) Summary: 1.

Open multiple traveling salesmen problem genetic algorithm in matlab

The following Matlab project contains the source code and Matlab examples used for open multiple traveling salesmen problem genetic algorithm. MTSPO_GA Open Multiple Traveling Salesmen Problem (M-TSP) Genetic Algorithm (GA)   Finds a (near) optimal solution to a variation of the M-TSP by setting   up a GA to search for the shortest route (least distance needed for the   salesmen to travel to each city exactly once without returning to their   starting location) Summary: 1.

Multiple variable traveling salesmen problem genetic algorithm in matlab

The following Matlab project contains the source code and Matlab examples used for multiple variable traveling salesmen problem genetic algorithm. MTSPV_GA Variable Multiple Traveling Salesmen Problem (M-TSP) Genetic Algorithm (GA)   Finds a (near) optimal solution to a variation of the M-TSP (that has a   variable number of salesmen) by setting up a GA to search for the   shortest route (least distance needed for the salesmen to travel to   each city exactly once and return to their starting locations) Summary: 1.

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