经典版本的分支定界法

B. Melnikov, E. Melnikova
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摘要

在计算机文献中,描述了许多可以称为离散优化问题的问题:从互联网上的信息加密(包括创建数字加密货币程序)到在社交网络中搜索“兴趣”组。通常,这些问题很难在计算机上解决,因此它们被称为“棘手的”。更准确地说,快速解决这些问题的可能方法很难解决(描述算法,编程);通常,蛮力解决方案编程简单,但相应的程序运行速度要慢得多。几乎所有这些棘手的问题都可以称为数学模型。同时,模型本身和为解决它而设计的算法通常都是为一个主题领域创建的,但它们也可以用于许多其他领域。这种模型的一个例子是旅行推销员问题。这个问题的特点是,考虑到它的公式相对简单,找到最优解(最优路线)。这个问题非常困难,属于所谓的np完全问题。此外,根据现有的分类,旅行推销员问题是优化问题的一个例子,而优化问题是该类中最复杂子类的一个例子。然而,本文的主要研究对象不是问题本身,而是问题的求解方法,即分支定界法。它由几个相关的启发式组成,在专著中,这种多启发式的分支定界方法显然以前没有注意到:算法和程序的开发人员应该自己理解这一点。同时,该方法本身也可以应用于许多其他离散优化问题。因此,经典版本的分支定界法是本文的主要内容,但同样重要的是经典表述中的第二个主题,即旅行商问题。本文讨论了分支定界法在求解旅行商问题中的应用,对于这种应用,我们也可以使用“经典”一词。然而,除了这个实现的经典版本之外,我们还考虑了一些新的启发式方法,这些方法与开发实时算法的需要有关。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
On the Classical Version of the Branch and Bound Method
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.
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