Aug 2026· Journal of university of Anbar for pure science· Vol 20, pp. 386-394· 0 citations· 20 references
TL;DR
The comparison suggests that CIH is more suitable for large-scale problems requiring quick solutions, whereas B&B is preferable when obtaining the optimal solution is essential, despite its higher computational cost and longer execution time.
Abstract
The Traveling Salesman Problem (TSP) is one of the most prominent combinatorial optimization problems, attracting significant interest in both research and practical applications. This paper compares the performance of two approaches for solving the TSP: the Cheapest Insertion Heuristic (CIH) and the Branch-and-Bound (B&B) algorithm. The results show that CIH produced a route of 584 km. This approach is simple and fast to execute, but it provides approximate solutions and does not guarantee optimality. In contrast, B&B was effective in finding the optimal solution by relying on lower-bound (LB) calculations and systematically eliminating nonpromising branches. The best route obtained using B&B was A → D → C → B → E → A. The comparison suggests that CIH is more suitable for large-scale problems requiring quick solutions, whereas B&B is preferable when obtaining the optimal solution is essential, despite its higher computational cost and longer execution time.
Weighted BOA∗ϵ (WBOA∗ ϵ), a weighted version of the BOA* algorithm, which uses two real parameters: a weight w for the heuristic and an approximation factor ϵ for the approximation factor, is introduced.
Hans Kühn Leiva, Jorge A. Baier, Carlos Hernández Ulloa et al.· Proceedings of the Thirty-Fi...· 0 citations
This work proposes an exact algorithm for the SSP, namely the Combinatorial Branch-and-Bound (C-B\&B) algorithm, which combines two distinct branch-and-bound algorithms, each introducing novel features compared with the existing literature.
Alberto Locatelli, Jean-François Côté, Leandro C. Coelho· 0 citations
These findings confirm that the strategic integration of distance-based crossover, diversified mutation methods, and complete 2-opt local search effectively navigates the complex search space, enabling highly efficient route determination for large-scale TSPs.
Rujira Jullapak, A. Thammano· HighTech and Innovation Jour...· 0 citations
Commonly used in math to discover the optimal solution to a problem with straight-line goals and limits is the technique of linear programming (LP). One of its first and most important applications is the Transport Problem (TP), which aims to find the best distribution strategy that meets supply and demand without sacr...
Farhana Rashid, Naeem Hossain, Jannatul Ferdous Jeba et al.· Jagannath University Journal...· 0 citations
In the traveling salesman problem, the aim is for a salesperson to start from one province, pass through each province only once, and come back to the same province. However, this problem can be reached by discovering the shortest possible route in total. When the number of provinces is large, it is a very difficult an...
R. Aşlıyan· Süleyman Demirel Üniversites...· 0 citations
The reviewed evidence indicates that metaheuristic approaches can provide flexible search mechanisms in computationally challenging settings, while learning-based models may support rapid inference, prediction, initialization, or search guidance when appropriate training data and generalization conditions are available...
S. El Kafhali, Mohamed Abid, Mohamed Hanini· Mathematical and Computation...· 1 citation
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