Coding Challenge #35.4: Traveling Salesperson with Genetic Algorithm
1,837In Part 1 of this multi-part coding challenge, I introduce the classic computer science problem of the Traveling Salesperson (TSP) and discuss the pitfalls with a brute force solution. In Part 2, I discuss Lexicographic Ordering and demonstrate one algorithm to iterate over all the permutations of an array. In Part 3, I apply this algorithm to a brute-force solution of the TSP problem. Every single route permutation is checked one by one. In Part 4, I attempt to create a solution to the TSP problem with a genetic algorithm, and then I add a “crossover” algorithm in Part 5. Code: https://thecodingtrain.com/challenges/35-traveling-salesperson
p5.js Web Editor Sketches:
🕹️ Part 1: Traveling Salesperson (TSP): https://editor.p5js.org/codingtrain/sketches/FCNAHaCqf
🕹️ Part 2: Lexicographic Order: https://editor.p5js.org/codingtrain/sketches/iYxi30gbl
🕹️ Part 3: TSP with Lexicographic Order: https://editor.p5js.org/codingtrain/sketches/bWPIkEv9s
🕹️ Part 4: TSP with Genetic Algorithm: https://editor.p5js.org/codingtrain/sketches/EGjTrkkf9
🕹️ Part 5: TSP with Genetic Algorithm and Crossover: https://editor.p5js.org/codingtrain/sketches/EGjTrkkf9
Other Parts of this Challenge:
📺 Part 1: Traveling Salesperson (TSP): https://youtu.be/BAejnwN4Ccw
📺 Part 2: Lexicographic Order: https://youtu.be/goUlyp4rwiU
📺 Part 3: TSP with Lexicographic Order: https://youtu.be/9Xy-LMAfglE
📺 Part 5: TSP with Genetic Algorithm and Crossover: https://youtu.be/hnxn6DtLYcY
🎥 Previous video: https://youtu.be/Cl_Gjj80gPE?list=PLRqwX-V7Uu6ZiZxtDDRCi6uhfTH4FilpH
🎥 Next video: https://youtu.be/rX5p-QRP6R4?list=PLRqwX-V7Uu6ZiZxtDDRCi6uhfTH4FilpH
🎥 All videos: https://www.youtube.com/playlist?list=PLRqwX-V7Uu6ZiZxtDDRCi6uhfTH4FilpH
References:
🌐 Traveling Salesman on Wikipedia: https://en.wikipedia.org/wiki/Travelling_salesman_problem
🗨️ Permutation Algorithm Using Lexicographic Ordering: https://www.quora.com/How-would-you-explain-an-algorithm-that-generates-permutations-using-lexicographic-ordering
📝 Array on MDN: https://developer.mozilla.org/en/docs/Web/JavaScript/Reference/Global_Objects/Array
📝 Array.includes() on MDN: https://developer.mozilla.org/en/docs/Web/JavaScript/Reference/Global_Objects/Array/includes
📝 Array.reverse() on MDN: https://developer.mozilla.org/en/docs/Web/JavaScript/Reference/Global_Objects/Array/reverse
📝 ES6 Sets on MDN: https://developer.mozilla.org/en/docs/Web/JavaScript/Reference/Global_Objects/Set
💾 The Nature of Code Part 2: https://github.com/shiffman/NOC-S17-2-Intelligence-Learning
📕 The Nature of Code: http://natureofcode.com/
Videos:
🎥 Improved Pool Selection: https://www.youtube.com/watch?v=ETphJASzYes&list=PLRqwX-V7Uu6YJ3XfHhT2Mm4Y5I99nrIKX&index=23
🎥 Genetic Algorithm Playlist: https://www.youtube.com/playlist?list=PLRqwX-V7Uu6bJM3VgzjNV5YxVxUwzALHV
🔴 Live Stream Archive #57: https://youtu.be/r_SpBy9fQuo
Related Coding Challenges:
🚂 #29 Smart Rockets in p5.js: https://youtu.be/bGz7mv2vD6g
🚂 #51 A* Pathfinding Algorithm: https://youtu.be/aKYlikFAV4k
🚂 #69 Evolutionary Steering Behaviors: https://youtu.be/flxOkx0yLrY
🚂 #70 Nearest Neighbors Recommendation Engine: https://youtu.be/N8Fabn1om2k
Timestamps:
00:00 Introducing Part 4
01:56 Code! Creating a population of orders
05:25 Shuffling the arrays of orders
09:45 Giving each order in the population a fitness score
11:17 Storing the order with the best fitness
13:17 Creating a new file for the Genetic Algorithm
14:08 Generating the next generation based on the best orders
18:59 Picking an order using pool selection based on their fitness
22:02 Mutating the picked orders
26:02 Debugging the code
27:12 Yay! This is working!
27:26 How to make the algorithm better?
Editing by Mathieu Blanchette
Animations by Jason Heglund
Music from Epidemic Sound
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🔗 p5.js: https://p5js.org
🔗 p5.js Web Editor: https://editor.p5js.org/
🔗 Processing: https://processing.org
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#travelingsalesperson #permutation #lexicographicordering #natureofcode #geneticalgorithm #evolution #bruteforce #factorial #arrays #p5js