[[["Easy to understand","easyToUnderstand","thumb-up"],["Solved my problem","solvedMyProblem","thumb-up"],["Other","otherUp","thumb-up"]],[["Missing the information I need","missingTheInformationINeed","thumb-down"],["Too complicated / too many steps","tooComplicatedTooManySteps","thumb-down"],["Out of date","outOfDate","thumb-down"],["Samples / code issue","samplesCodeIssue","thumb-down"],["Other","otherDown","thumb-down"]],["Last updated 2024-08-06 UTC."],[[["\u003cp\u003e\u003ccode\u003eHeldWolfeCrowderEvaluator\u003c/code\u003e is a C++ class used in calculating the Held-Karp lower bound for the Traveling Salesperson Problem (TSP).\u003c/p\u003e\n"],["\u003cp\u003eIt utilizes methods like \u003ccode\u003eGetStep\u003c/code\u003e, \u003ccode\u003eNext\u003c/code\u003e, \u003ccode\u003eOnNewWMax\u003c/code\u003e, and \u003ccode\u003eOnOneTree\u003c/code\u003e to iteratively refine the lower bound.\u003c/p\u003e\n"],["\u003cp\u003eThe constructor for this class requires the number of nodes and a cost function to represent the TSP instance.\u003c/p\u003e\n"],["\u003cp\u003eThis class focuses on efficiently finding a lower bound for the optimal TSP solution, not the solution itself.\u003c/p\u003e\n"]]],["The `HeldWolfeCrowderEvaluator` class in C++ provides methods for evaluating and managing a lower bound calculation. Key actions include: initializing the evaluator with a number of nodes and a cost function (`HeldWolfeCrowderEvaluator`), iterating through steps (`Next`), retrieving the current step value (`GetStep`), updating with a new maximum value (`OnNewWMax`), and updating when a new one-tree cost is calculated (`OnOneTree`) passing the cost, w, and degrees. Each method has specific return types and arguments.\n"],null,[]]
