Distribution centers (DCs) play important role in maintaining the uninterrupted flow of goods and materials between the manufacturers and their customers.This paper proposes a mathematical model as the bi-objective capacitated multi-vehicle allocation of customers to distribution centers. An evolutionary algorithm named non-dominated sorting ant colony optimization (NSACO) is used as the optimi...

Research efforts in metaheuristics have shown that an intelligent incorporation of more classical optimization techniques in metaheuristics can be very beneficial. In this paper, we combine the metaheuristic ant colony optimization with dynamic programming for the application to the NP-hard k-cardinality tree problem. Given an undirected graph G with node and/or edge weights, the problem consis...

Ant Colony Optimization is a probabilistic technique for finding the optimal path for reaching a destination using graphs. This algorithm was further developed to introduce the concept of Multiple Ant Colony Optimization technique in which ants were classified into various families that worked to provide optimal path solutions to the destination for their own family. This paper aims at proposin...

Every insect is considered, from the viewpoint of biological evolution, to be a neural cell that constitutes a neural network in a casual and loose way of joint. Through simulating the ant swarm intelligence on the basis of human neural network, this paper advances a linear binary network. The binary code expects a low intelligence of each ant, and each path corresponds to a comparatively small...

The combination of traditional ant colony algorithm in solving the optimization process to consume a large amount of time, easily falling into local optimal solution and convergence is slow and other disadvantages, while also generating a lot of useless redundant iterative code, operation efficiency is low. Therefore, ant colony optimization algorithm is proposed. The algorithm based on genetic...

Parallel algorithms, such as the ant colony algorithm, take a long time when solving large-scale problems. In this paper, the MAX-MIN Ant System algorithm (MMAS) is parallelized to solve Traveling Salesman Problem (TSP) based on a Spark cloud computing platform. We combine MMAS with Spark MapReduce to execute the path building and the pheromone operation in a distributed computer cluster. To im...

proposed to improve the performance of the ACO algorithm. In this paper an ant colony optimization with memory is proposed, which is applied to the classical traveling salesman problem (TSP). In the proposed algorithm, each ant searches the solution not only according to the pheromone and heuristic information but also based on the memory which is from the solution of the last iteration. A larg...

In this paper, a new algorithm for solving the single loop routing problem is presented. The purpose of the single loop routing problem(SLRP) is to find the shortest loop for an automated guided vehicle covering at least one edge of each department of a block layout. First it shown that this problem can be represented as a graph model. Then a meta-heuristic algorithm based on and colony system ...

Ant miner is a data mining algorithm based on Ant Colony Optimization (ACO). Ant miner algorithms are mainly for discovery rule for optimization. Ant miner + algorithm uses MAX-MIN ant system for discover rules in the database. Soil classification deals with the systematic categorization of soils based on distinguished characteristics as well as criteria. The proposed model delivers to Ant mine...

Images which are captured in outdoor scenes often degrade in quality due to atmospheric conditions induced by suspending particles like mist, haze, fog, etc. which scatter and absorb light before it reaches to the camera. The weather-degraded images directly affect the efficiency of computerized surveillance and monitoring system. In this paper, we propose an efficient haze removal technique wh...