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 QAP is considered one of the most complex combinatorial optimization problems and it is the model for many real life problems such as facilities location, camp planning, computer keyboard design and electronic boards cabling, among other applications. This Paper solves some significant instances of this problem through an improved Parallel Genetic Algorithm based Grid by means of the local ...

Many real world industrial applications involve finding a Hamiltonian path with minimum cost. Some instances that belong to this category are transportation routing problem, scan chain optimization and drilling problem in integrated circuit testing and production. Distributed learning automata, that is a general searching tool and is a solving tool for variety of NP-complete problems, together ...

Ant colony optimization (ACO) is a stochastic search method for solving NP-hard problems. The exploration versus exploitation dilemma rises in ACO search. Reactive max-min ant system algorithm is a recent proposition to automate the exploration and exploitation. It memorizes the search regions in terms of reactive heuristics to be harnessed after restart, which is to avoid the arbitrary explora...

This paper presents an empirical analysis of some implementations of tour improvement heuristics designed for the pickup and delivery traveling salesman problem. Results show that while the classical 2-opt traveling salesman algorithm can be implemented very efficiently, available implementations of the 3-opt are much less efficient. Among tested algorithms, the only one to produce significant ...

The problems with high complexity had been the challenge in combinatorial problems. Due to the none-determined and polynomial characteristics, these problems usually face to unreasonable searching budget. Hence combinatorial optimizations attracted numerous researchers to develop better algorithms. In recent academic researches, most focus on developing to enhance the conventional evolutional a...

A combinatorial auction is an auction where the bidders have the choice to bid on bundles of items. The WDP in combinatorial auctions is the problem of finding winning bids that maximize the auctioneer’s revenue under the constraint that each item can be allocated to at most one bidder. The WDP is known as an NP-hard problem with practical applications like electronic commerce, production manag...

This paper proposes a new two-phase hybrid metaheuristic for vehicle routing problem with time windows (VRPTW). The first phase is to minimize the number of routes by means of variable neighborhood search algorithm, while the second phase is mainly aimed at minimizing the total travel distance using tabu search algorithm. Three neighborhood search operators (All-exchange, All-2-opt, All-crossex...

Purpose: In this paper, we consider the maximum traveling salesman problem, a variation of the usual traveling salesman problem, in which the objective is to maximize the cost of a tour of the salesman. The main purpose of this paper is to develop a hybrid genetic algorithm (GA) for obtaining a heuristically optimal solution to the problem. Methods: First, a simple GA and then a hybrid GA have ...

Several variants and generalizations of the Or-opt heuristic for the Symmetric Traveling Salesman Problem are developed and compared on random and planar instances. Some of the proposed algorithms are shown to significantly improve upon the standard 2-opt and Or-opt heuristics.