The Travelling Salesman Problem (TSP) is one of the most studied combinatorial optimization problem which is significant in many practical applications in transportation field. The TSP is an NP-hard problem and requires large computational power to be optimally solved by exact algorithms. In the past few years, fast development of generalpurpose Graphics Processing Units (GPUs) has brought huge...

Ant Colony Extended (ACE) is a novel algorithm belonging to the general Ant Colony Optimisation (ACO) framework. Two specific features of ACE are: the division of tasks between two kinds of ants, namely patrollers and foragers, and the implementation of a regulation policy to control the number of each kind of ant during the searching process. In addition, ACE does not employ the construction g...

Derived from the well-known Traveling Salesman problem (TSP), the multiple-Traveling Salesman problem (multiple-TSP) with single depot is a straightforward generalization: several salesmen located in a given city (the depot) need to visit a set of interconnected cities, such that each city is visited exactly once (by a single salesman) while the total cost of their tours is minimized. Designed ...

In built infrastructure monitoring, an efficient path planning algorithm is essential for robotic inspection of large surfaces using computer vision. In this work, we first formulate the inspection path planning problem as an extended travelling salesman problem (TSP) in which both the coverage and obstacle avoidance were taken into account. An enhanced discrete particle swarm optimisation (DPS...

A genetic algorithm (GA) has several genetic operators that can be modified to improve the performance of particular implementations. These operators include parent selection, crossover and mutation. Selection is one of the important operations in the GA process. There are several ways for selection. This paper presents the comparison of GA performance in solving travelling salesman problem (TS...

Among numerous NP-hard problems, the Traveling Salesman Problem (TSP) has been one of the most explored, yet unknown one. Even a minor modification changes the problem’s status, calling for a different solution. The Generalized Traveling Salesman Problem (GTSP)expands the TSP to a much more complicated form, replacing single nodes with a group or cluster of nodes, where the objective is to fi...

The Traveling Salesman Problem is one of the best studied NP-hard problems in combinatorial optimization. Powerful methods have been developed over the last 60 years to find optimum solutions to large TSP instances. The largest TSP instance so far that has been solved optimally has 85,900 vertices. Its solution required more than 136 years of total CPU time using the branch-and-cut based Concor...

This paper explores new experimental evidence examining the relationship between cases and result quality in Case-Based Reasoning systems where adaptation is involved. This evidence comes from two domains; a Travelling Salesman Problem (TSP) solver and a system devising Nurse Rosters. It concludes that there is no simple relationship between cases and problems that can guarantee solution qualit...

The Quadratic Travelling Salesman Problem (QTSP) is to find a least cost Hamiltonian cycle in an edge-weighted graph, where costs are defined for all pairs of edges contained in the Hamiltonian cycle. The problem is shown to be strongly NP-hard on a Halin graph. We also consider a variation of the QTSP, called the k-neighbour TSP (TSP(k)). Two edges e and f , e 6= f , are k-neighbours on a tour...