Coding Challenge #35.5: TSP with Genetic Algorithm and Crossover

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The Coding Train

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Published on May 2, 2017 2:15:24 PM ● Video Link: https://www.youtube.com/watch?v=hnxn6DtLYcY

Duration: 23:09

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In 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 4: TSP with Genetic Algorithm: https://youtu.be/M3KTWnTrU_c

🎥 Previous video: https://youtu.be/Cl_Gjj80gPE?list=PLRqwX-V7Uu6ZiZxtDDRCi6uhfTH4FilpH
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🎥 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 Recap from Part 4
00:35 What is crossover?
02:33 Improvement: showing the algorithm running
04:24 Improvement: adding a mutation rate
06:08 Where to apply crossover in the code?
07:10 How to apply crossover?
11:08 Code! Implementing the crossOver() function
15:30 Testing the crossOver() function
16:13 Playing with the variables
17:45 About the ES6 includes() function and Set
18:03 Inefficiency of the dist() function
18:44 Suggestion to improve mutation
21:10 Please share your own variations and improvements!

Editing by Mathieu Blanchette
Animations by Jason Heglund
Music from Epidemic Sound

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#travelingsalesperson #permutation #lexicographicordering #natureofcode #geneticalgorithm #evolution #bruteforce #factorial #arrays #p5js