Research on Heuristics Logistics Distribution Algorithm Based on Parallel Multi-ant Colonies

Tang, Ruixue; Qin, Yongbin; Zhang, Li

doi:10.4304/jsw.6.4.612-619

Cited by 6 publications

(3 citation statements)

References 12 publications

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“…Ant Colony Optimization (ACO) [18,19] algorithm is a new kind of simulated evolutionary algorithm [20] and it has been successfully applied to several NP-hard combinatorial optimization problems [21] . The ACO algorithm was proposed by Italian scholar M. Dorigo according to food-seeking behavior by ants in 1996 [22] .…”

Section: A Ant Colony Optimization Algorithmmentioning

confidence: 99%

An ACO-LB Algorithm for Task Scheduling in the Cloud Environment

Xue

et al. 2014

JSW

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In the face of a large number of task requests which are submitted by users, the cloud data centers need not only to finish these massive tasks but also to satisfy the user's service demand. How to allocate virtual machine reasonably and schedule the tasks efficiently becomes a key problem to be solved in the cloud environment. This paper proposes a ACO-LB(Load balancing optimization algorithm based on ant colony algorithm) algorithm to solve the load imbalance of virtual machine in the process of task scheduling .The ACO-LB algorithm can adapt to the dynamic cloud environment. It will not only shorten the makespan of task scheduling, but also maintain the load balance of virtual machines in the data center. In this paper, the workflow scheduling is simulated in CloudSim. The results show that the proposed ACO-LB algorithm has better performance and load balancing ability.

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Section: A Ant Colony Optimization Algorithmmentioning

confidence: 99%

An ACO-LB Algorithm for Task Scheduling in the Cloud Environment

Xue

et al. 2014

JSW

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“…ACO integrate the information of the partly and global, weight the important of the information, then choose the optimal path. This method can integrates the partly optimal path to the global optimal path and get the shortest distance, which has been widely used in many fields such as supply chain design [12][13][14][15][16], robot learning and planning [17,18], customer behavior analysis [19,20], job shop scheduling problem [21,22], financial forecast [23], signal processing [24], power system design [25], and so. In this paper we take the total cost as the total distance, take the several cost as points, the amount of the cost as the road distance which are vary with the candidate solution, using the ACO to calculate the best solution.…”

Section: Ant Colony Optimization For Solving the Problemmentioning

confidence: 99%

A Model for Creative Products to Forecast and It’s Production Plan Solved by ACO

Zeng¹,

Chen²

2013

JCP

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Creative product is special product, which has characteristics like short product life cycle, big market risk and so on. The market is changed very soon, and the needs of customers are changed quickly, too. In order to increase the profit and decrease the cost, it is necessary to forecast the demand and make production plan. The product plan is developed according to the quantity of demand, but creative product has no historical sell data to base on, what's more, the demand is unknowable, the information of market is delayed, so it's difficult to forecast accurately. Trend Extrapolation is a way to forecast, and there are many models such as The Gompertz Curve and Pearl curve. The Gompertz curve is used to analysis the development, progress, maturity and decline of new products which is consist with the several stage of product life cycle, the author will use it to forecast, then make production plan of it and use ant colony optimization (ACO) to find the best answer.

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“…Describe of ant colony algorithm. The ant colony algorithm in the calculation of the cycle must obey the following rules [6]: (a) The rule of state transition In the site r, the calculation about probability of ant k chooses to transfer to the site s is:…”

Section: Algorithm Solvingmentioning

confidence: 99%

Study on Optimization Model of Multiple Depot Vehicle Scheduling in Logistics Distribution of Expressway Service Area

Zhou

Li³

2012

AMM

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Based on the unblocked reliability theory of the road network, combined with the characteristics of the logistics distribution of expressway service areas, the concept of network unblocked reliability on logistics distribution was put forward. Under the reliability analysis, the optimization model of multi objective, multi depot and open vehicle scheduling on logistics distribution of highway service areas was established, and the ant colony algorithm was designed. In the end an example was analyzed to validate the usability of the optimization model by comparing with saving mileage, which demonstrates the established optimization model of multiple depot vehicle scheduling is of a better practical value to guide the optimization decision making of logistics distribution network and to improve the reliability of logistics distribution of expressway service areas.

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Research on Heuristics Logistics Distribution Algorithm Based on Parallel Multi-ant Colonies

Cited by 6 publications

References 12 publications

An ACO-LB Algorithm for Task Scheduling in the Cloud Environment

An ACO-LB Algorithm for Task Scheduling in the Cloud Environment

A Model for Creative Products to Forecast and It’s Production Plan Solved by ACO

Study on Optimization Model of Multiple Depot Vehicle Scheduling in Logistics Distribution of Expressway Service Area

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