This study focuses on the home health care routing problem (HHCRP) in scenario of high population density areas where many elders live closely together. considers two main objectives. The first is to reduce travel and wait times for nurses or elders. second concerns socially related objectives scheduling problems, such as ‘quality life’ empowerment, by considering assumptions acquaintanceship m...

This article puts forward the routing algorithm of wireless sensor network based on ant colony optimization. The algorithm uses the characteristics of ant colony algorithm that is easy to realize local work, integrates link quality into the pheromone formation and supports multiple routes. When choosing routing, the probability is calculated that the node is selected as the next hop according t...

In this paper we present two versions of AntNet, a novel approach to adaptive learning of routing tables in wide area best-effort datagram networks. AntNet is a distributed multi-agent system inspired by the stigmergy model of communication observed in ant colonies. We report simulation results for AntNet on realistically sized networks using as performance measures throughput, packet delays an...

Ant colony optimization algorithm is a way to be used to find the optimal solutions is enormous, the number of ants on the path, which will lead to reduced the network node on the path energy drastically. The wireless sensor network is a large number of tiny sensor nodes with communication and computing power. Using wireless sensor networks collaboration to perception, the perception of the obj...

One of the most important extensions of the capacitated vehicle routing problem (CVRP) is the vehicle routing problem with simultaneous pickup and delivery (VRPSPD) where customers require simultaneous delivery and pick-up service. In this paper, we propose an effective ant colony optimization (EACO) which includes insert, swap and 2-Opt moves for solving VRPSPD that is different with common an...

Job scheduling is one of the main factors affecting grid computing performance. Job scheduling problem classified as an NP-hard problem. Such a problem can be solved only by using approximate algorithms such as heuristic and meta-heuristic algorithms. Ant colony system algorithm is a meta-heuristic algorithm which has the ability to solve differenttypes of NP-hard problems.However, ant colony s...

This paper investigates a comparative study which addresses the P/prec/Cmax scheduling problem, a notable NP-hard benchmark. MLP_SACS, a modified ant colony algorithm, is used to solve it. Its application provides us a better job allocation to machines. In front of each machine, the jobs are performed with three priority rules, the longest path (LP), a modified longest path (MLP) and a maximum ...

This paper presents an application of the ant colony metaphor for continuous space optimization problems. The ant algortihm proposed works following the principle of the ant colony approach, i.e., a population of agents iteratively, cooperatively, and independently search for a solution. Each ant in the distributed algorithm applies a local search operator which explores the neighborhood region...

The Multi-Depot Vehicle Routing Problem (MDVRP) is a generalization of SDVRP, in which multiple vehicles start from multiple depots and return to their original depots at the end of their assigned tours. The MDVRP is NP-hard, therefore, the development of heuristic algorithms for this problem class is of primary interest. This paper solves Multi-Depot Vehicle Routing Problem with Cellular Ant A...

Aimed at the problems that classical ant colony algorithm is easy to fall into local optimal, this thesis puts forward a new AODV routing protocol based on improved geneticant colony algorithms (IGAACA-AODV) by introducing genetic algorithm (GA) to improve ant colony algorithm, and combining with the characteristics of AODV routing protocols in Ad Hoc network. First of all, the proposed algorit...