scholarly journals Modified Traveling Salesman Problem for a Group of Intelligent Mobile Objects and Method for Its Solving

Author(s):  
Vitalii Tkachov ◽  
◽  
Volodymyr Tokariev ◽  
Iryna Ilina ◽  
Stanislav Partyka

A solution of a modified traveling salesman problem for the case, in which a group of intelligent mobile objects is simultaneously involved, is discussed in the article. For this purpose, a review and a comparative analysis of Johnson's algorithms and the branch and bound method have been carried out. It was found that these algorithms are ineffective for solving the modified traveling salesman problem for a group of intelligent mobile objects, therefore, a quest method has been further developed as a solution to this problem. The results of experimental calculations are presented. The directions of further work on the unification of the developed method for constructing structures of fast step-by-step data processing are proposed. 

2021 ◽  
pp. 21-44
Author(s):  
Boris Melnikov ◽  
◽  
Elena Melnikova ◽  

In the computer literature, a lot of problems are described that can be called discrete optimization problems: from encrypting information on the Internet (including creating programs for digital cryptocurrencies) before searching for “interests” groups in social networks. Often, these problems are very difficult to solve on a computer, hence they are called “intractable”. More precisely, the possible approaches to quickly solving these problems are difficult to solve (to describe algorithms, to program); the brute force solution, as a rule, is programmed simply, but the corresponding program works much slower. Almost every one of these intractable problems can be called a mathematical model. At the same time, both the model itself and the algorithms designed to solve it are often created for one subject area, but they can also be used in many other areas. An example of such a model is the traveling salesman problem. The peculiarity of the problem is that, given the relative simplicity of its formulation, finding the optimal solution (the optimal route). This problem is very difficult and belongs to the so-called class of NP-complete problems. Moreover, according to the existing classification, the traveling salesman problem is an example of an optimization problem that is an example of the most complex subclass of this class. However, the main subject of the paper is not the problem, but the method of its soluti- on, i.e. the branch and bound method. It consists of several related heuristics, and in the monographs, such a multi-heuristic branch and bound method was apparently not previously noted: the developers of algorithms and programs should have understood this themselves. At the same time, the method itself can be applied (with minor changes) to many other discrete optimization problems. So, the classical version of branch and bound method is the main subject of this paper, but also important is the second subject, i.e. the traveling salesman problem, also in the classical formulation. The paper deals with the application of the branch and bound method in solving the traveling salesman problem, and about this application, we can also use the word “classical”. However, in addition to the classic version of this implementation, we consider some new heuristics, related to the need to develop real-time algorithms.


2021 ◽  
Vol 27 (1) ◽  
pp. 3-8
Author(s):  
M. V. Ulyanov ◽  
◽  
M. I. Fomichev ◽  
◽  
◽  
...  

The exact algorithm that implements the Branch and Boimd method with precomputed tour which is calculated by Lin-Kernighan-Helsgaun metaheuristic algorithm for solving the Traveling Salesman Problem is concerned here. Reducing the number of decision tree nodes, which are created by the Branches and Bound method, due to a "good" precomputed tour leads to the classical balancing dilemma of time costs. A tour that is close to optimal one takes time, even when the Lin-Kernighan-Helsgaun algorithm is used, however it reduces the working time of the Branch and Bound method. The problem of determining the scope of such a combined algorithm arises. In this article it is solved by using a special characteristic of the individual Traveling Salesman Problem — the number of changes tracing direction in the search decision tree generated by the Branch and Bound Method. The use of this characteristic allowed to divide individual tasks into three categories, for which, based on experimental data, recommendations of the combined algorithm usage are formulated. Based on the data obtained in a computational experiment (in range from 30 to 45), it is recommended to use a combined algorithm for category III problems starting with n = 36, and for category II problems starting with n = 42.


2019 ◽  
Vol 31 (2) ◽  
pp. 335-346 ◽  
Author(s):  
Stefan Poikonen ◽  
Bruce Golden ◽  
Edward A. Wasil

1998 ◽  
Vol 08 (01) ◽  
pp. 41-50
Author(s):  
Yung-Syau Chen ◽  
Jean-Luc Gaudiot

Parallel branch-and-bound is an optimization technique which renders more efficient the solution of some hard problems such as the puzzle of colored blocks and the traveling-salesman problem. In a functional language such as Sisal 2.0, it is difficult for the programmer to describe a parallel version of this technique due to the lack of imperative features in the language. In this paper, we propose a version of Sisal 2.0 extended with user-declared mutable global variables in order to enable Sisal programmers to apply the parallel branch-and-bound technique. In a simple example (the puzzle of colored blocks), we show that this approach yields better performance than either conventional functional programs or imperative programs. It is easy to see that the same strategy can be used to solve a number of hard problems such as the traveling-salesman problem.


2021 ◽  
Vol 12 (2) ◽  
pp. 198-189
Author(s):  
Agung Chandra ◽  
Christine Natalia

Research of travel distance on single - depot position in warehouse is tremendous. This study focuses more on the effect of two-depot position on travel distance in order picking problem (OPP) by using the concept of traveling salesman problem (TSP) and exact method – Branch and Bound (B\&B) algorithm. The total distance of one-depot position is shorter than two-depot position for single and double block warehouses and the difference is less than 5%. The total distance is also compared with approximate methods – SA and TS which show that the differences are less than 5%. The sequence of location visit for one depot and two depot is similar about two third from the total location visits. For order picking problem that has more than 25 location visits, one need to consider to apply approximate approach to get the solution faster even the difference will be higher from exact approach when the number of location visit or aisle increases.


2018 ◽  
Vol 16 (1) ◽  
pp. 15
Author(s):  
Karina Auliasari ◽  
Mariza Kertaningtyas ◽  
Diah Wilis Lestarining Basuki

Permasalahan yang sering terjadi dalam proses pendistribusian produk pada perusahaan ini adalah belum optimalnya rute pendistribusian produk sehingga seringkali terjadi perubahan rute dan penjadwalan ulang pengiriman produk. Hal ini terjadi karena pihak manajemen pemasaran belum mengaplikasikan suatu metode optimalisasi dan belum adanya dukunga terkomputerisasi untuk menghasilkan informasi yang mendukung dalam pengambilan keputusan rute distribusi. Tujuan diterapkannya metode traveling salesman problem (TSP) adalah memberikan pilihan solusi rute distribusi yang dapat meminimalisir keterlambatan pengiriman barang dan mengoptimalkan sarana transportasi, sumber daya manusia, waktu dan biaya yang dimiliki untuk mengirimkan produk. Berdasarkan hasil uji performa penerapan metode TSP menunjukkan bahwa menggunakan parameter jarak dan waktu tempuh maka dapat dihasilkan pilihan dua rute pengiriman yang berbeda. Pilihan dua rute yang dihasilkan dari komputerisasi menggunakan metode TSP dengan teknik branch and bound dilengkapi dengan penyajian pohon keputusan dari titik awal hingga titik tujuan yang pada akhirnya membentuk rute yang optimal.


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