This paper solves the dynamic traveling salesman problem (DTSP) using dynamic Gaussian Process Regression (DGPR) method. The problem of varying correlation tour is alleviated by the nonstationary covariance function interleaved with DGPR to generate a predictive distribution for DTSP tour. This approach is conjoined with Nearest Neighbor (NN) method and the iterated local search to track dynami...

The traveling salesman problem (TSP) belongs to the most basic, most important, and most investigated problems in combinatorial optimization. Although it is an NP-hard problem, many of its special cases can be solved efficiently in polynomial time. We survey these special cases with emphasis on the results that have been obtained during the decade 1985–1995. This survey complements an earlier s...

This paper describes a polynomial transformation for a class of unit-demand vehicle routing problems, named node-balanced routing problems (BRP), where the number of nodes on each route is restricted to be in an interval such that the workload across the routes is balanced. The transformation is general in that it can be applied to single or multiple depot, homogeneous or heterogeneous fleet BR...

The traveling salesman problem (TSP) has been an extensively studied problem for a long time and has attracted a considerable amount of research effort. Ant colony system (ACS) algorithm is better method to solve TSP. This paper presents HACS-LS, a hybrid ant colony optimization approach combined with an improvement local search algorithm, applied to traveling salesman problem. The improvement ...

The author would like to propose a simple but yet effective method, convex layers, nearest neighbor and triangle inequality, to approach the Traveling Salesman Problem (TSP). No computer is needed in this method. This method is designed for plain folks who faced the TSP everyday but do not have the sophisticated knowledge of computer science, programming language or applied mathematics. The aut...

PT XYZ as the best and largest Bed Sheet Set company in Indonesia with products such Covers, Sheets, Pillowcases, Bolsters Blankets. The Traveling Salesman Problem (TSP) is a problem faced finding route to visit shops that sell from BIG. A shop carried out on condition each city can only be visited once except of origin. algorithms applied this TSP include Complete Enumeration, Branch & Bou...

In the 2-period Balanced Traveling Salesman Problem (2B-TSP), the customers must be visited over a period of two days: some must be visited daily, and the others on alternate days (even or odd days); moreover, the number of customers visited in every tour must be ‘balanced’, i.e. it must be the same or, alternatively, the difference between the maximum and the minimum number of visited customer...

Gottschalk and Vygen proved that every solution of the well-known subtour elimination linear program for traveling salesman paths is a convex combination of a set of more and more restrictive “generalized Gao trees” of the underlying graph. In this paper we give a short proof of this, as a layered convex combination of bases of a sequence of more and more restrictive matroids. Our proof implies...

We present approximation algorithms for almost all variants of the multi-criteria traveling salesman problem (TSP). First, we devise randomized approximation algorithms for multi-criteria maximum traveling salesman problems (Max-TSP). For multi-criteria Max-STSP, where the edge weights have to be symmetric, we devise an algorithm with an approximation ratio of 2/3 − ε. For multi-criteria Max-AT...

Imperial competitive algorithm (ICA) simulates a multi-agent algorithm. Each agent is like a kingdom has its country, and the strongest country in each agent is called imperialist, others are colony. Countries are competitive with imperialist which in the same kingdom by evolving. So this country will move in the search space to find better solutions with higher fitness to be a new imperialist....