Comparative study of pheromone control heuristics in ACO algorithms for solving RCPSP problems

González-Pardo, Antonio; Ser, Javier Del; Camacho, David

doi:10.1016/j.asoc.2017.06.042

Cited by 33 publications

(28 citation statements)

References 39 publications

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“…At that point, this diagram portrayal can be clustered into node groups in light of the topology data of the chart, where each group incorporates emphatically interconnected vertices. 21 The results recommend that the impacts of behavior spread on social networks are firmly content dependent. It works in two phases; in the underlying stage, the nodes are partitioned into gatherings, and in the later stage, endeavors are made to keep up the structure made in the first stage.…”

Section: Introductionmentioning

confidence: 90%

Efficient artificial fish swarm based clustering approach on mobility aware energy‐efficient for MANET

Gupta

Khanna

Lakshmanaprabu

et al. 2018

Trans Emerging Tel Tech

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Mobile ad hoc network (MANET) is a gathering of self‐ruling mobile nodes in which ad hoc network framed without settled foundation. Dynamic topology property of MANET may debase the execution of the network, mobility attentiveness, and energy effectiveness because of an ideal cluster head (CH). The low energy adaptive clustering hierarchy protocol is used in the MANETs for enhancement of network life time by proficiently utilizing of the accessible constrained energy. Artificial fish swarm optimization is used to select the CH in MANET communication process. The election of CH takes care of mobility and remaining energy as well as the degree of connectivity for selecting nodes to serve as cluster for longer duration of time. From the implementation results, it is observed that the proposed method provides the maximum network life time as 80 to 140 hours and minimum energy consumption as 9 to 130 J, compared with existing protocol and optimization technique.

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Section: Introductionmentioning

confidence: 90%

Efficient artificial fish swarm based clustering approach on mobility aware energy‐efficient for MANET

Gupta

Khanna

Lakshmanaprabu

et al. 2018

Trans Emerging Tel Tech

View full text Add to dashboard Cite

show abstract

“…Fog node chain and its communications, as shown in Fig. 1 is constructed by choosing the furthest fog node from the cloud computing using equation (15) and (16), to ensure that fog nodes further from the cloud computing have close neighbours. The neighbouring distances increase progressively since fog nodes already on the chain cannot be revisited.…”

Section: Data Transmission Between Fog Nodes and Data Centrementioning

confidence: 99%

“…They deposit a chemical substance called pheromone on their path as they traverse the network. This method has been used to solve many optimization problems in WSNs [15][16][17]. among the nodes.…”

Section: Introductionmentioning

confidence: 99%

Energy-efficient hierarchical routing in wireless sensor networks based on Fog Computing

Abidoye

Kabaso

2020

Preprint

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Wireless sensor networks (WSNs) have been recognized as one of the most essential technologies of the 21st century. The applications of WSNs are rapidly increasing in almost every sector because they can be deployed in areas where cable and power supply are difficult to use. In the literature, different methods have been proposed to minimize energy consumption of sensor nodes so as to prolong WSNs utilization. In this article, we propose an efficient routing protocol for data transmission in WSNs; it is called Energy-Efficient Hierarchical routing protocol for wireless sensor networks based on Fog Computing (EEHFC). Fog computing is integrated into the proposed scheme due to its capability to optimize the limited power source of WSNs and its ability to scale up to the requirements of the Internet of Things applications. In addition, we propose an improved ant colony optimization (ACO) algorithm that can be used to construct optimal path for efficient data transmission for sensor nodes. The performance of the proposed scheme is evaluated in comparison with P-SEP, EDCF, and RABACO schemes. The results of the simulations show that the proposed approach can minimize sensor nodes’ energy consumption, data packet losses and extends the network lifetime

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“…The priority rule-based construction heuristic is widely used in RCPSP to generate feasible initial schedules. Then, the obtained schedules are improved by various neighbourhood search methods and meta-heuristic algorithm, including tabu search [9], simulated annealing [10], scatter search [11], ant colony optimization [12], particle swarm optimization [13], and genetic algorithm [14][15][16].…”

Section: Introductionmentioning

confidence: 99%

A Building‐Block‐Based Genetic Algorithm for Solving the Robots Allocation Problem in a Robotic Mobile Fulfilment System

Zhang

Weng

2019

Mathematical Problems in Engineering

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Robotic mobile fulfilment system (RMFS) is an efficient and flexible order picking system where robots ship the movable shelves with items to the picking stations. This innovative parts-to-picker system, known as Kiva system, is especially suited for e-commerce fulfilment centres and has been widely used in practice. However, there are lots of resource allocation problems in RMFS. The robots allocation problem of deciding which robot will be allocated to a delivery task has a significant impact on the productivity of the whole system. We model this problem as a resource-constrained project scheduling problem with transfer times (RCPSPTT) based on the accurate analysis of driving and delivering behaviour of robots. A dedicated serial schedule generation scheme and a genetic algorithm using building-blocks-based crossover (BBX) operator are proposed to solve this problem. The designed algorithm can be combined into a dynamic scheduling structure or used as the basis of calculation for other allocation problems. Experiment instances are generated based on the characteristics of RMFS, and the computation results show that the proposed algorithm outperforms the traditional rule-based scheduling method. The BBX operator is rapid and efficient which performs better than several classic and competitive crossover operators.

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Comparative study of pheromone control heuristics in ACO algorithms for solving RCPSP problems

Cited by 33 publications

References 39 publications

Efficient artificial fish swarm based clustering approach on mobility aware energy‐efficient for MANET

Efficient artificial fish swarm based clustering approach on mobility aware energy‐efficient for MANET

Energy-efficient hierarchical routing in wireless sensor networks based on Fog Computing

A Building‐Block‐Based Genetic Algorithm for Solving the Robots Allocation Problem in a Robotic Mobile Fulfilment System

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