An improved artificial bee colony algorithm for pavement resurfacing problem

Panda, Tapas Ranjan; Swamy, Aravind Krishna

doi:10.1016/j.ijprt.2018.04.001

Cited by 16 publications

(6 citation statements)

References 14 publications

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“…However, the optimization effect of the algorithm is not good when solving high-dimensional and multi-objective problems. In another work, an improved artificial bee colony algorithm was proposed to address the pavement resurfacing optimization problem (Panda & Swamy, 2018). However, this algorithm is prone to fall into a local optimum and the convergence rate is slow in the later evolution.…”

Section: Literature Reviewmentioning

confidence: 99%

An Integrated Multi-Objectives Optimization Approach on Modelling Pavement Maintenance Strategies for Pavement Sustainability

Xue

Wang

et al. 2020

Journal of Civil Engineering and Management

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Addressing the multi-dimensional challenges to promote pavement sustainability requires the development of an optimization approach by simultaneously taking into account future pavement conditions for pavement maintenance with the capability to search and determine optimal pavement maintenance strategies. Thus, this research presents an integrated approach based on the Markov chain and Particle swarm optimization algorithm which aims to consider the predicted pavement condition and optimize the pavement maintenance strategies during operation when applied in the maintenance management of a road pavement section. A case study is conducted for testing the capability of the proposed integrated approach based on two maintenance perspectives. For case 1, maintenance activities mainly occur in TM20, TM31, and TM41, with the maximum maintenance mileage reaching 88.49 miles, 50.89 miles, and 20.91 miles, respectively. For case 2, the largest annual maintenance cost in the first year is $15.16 million with four types of maintenance activities. Thereafter, the maintenance activities are performed at TM10, TM31, and TM41, respectively. The results obtained, compared with the linear program, show the integrated approach is effective and reliable for determining the maintenance strategy that can be employed to promote pavement sustainability.

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Section: Literature Reviewmentioning

confidence: 99%

An Integrated Multi-Objectives Optimization Approach on Modelling Pavement Maintenance Strategies for Pavement Sustainability

Xue

Wang

et al. 2020

Journal of Civil Engineering and Management

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“…In the transportation field, Wang and Leong found ABC the most efficient optimization algorithm for finding the optimal routes in transit systems ( 18 ). Panda and Swamy proposed ABC for pavement resurfacing optimization to find the best resurfacing frequency intensity efficiently ( 19 ). Sharma et al tackled the use of ABC in the cost optimization of construction projects ( 20 ).…”

Section: Literature Reviewmentioning

confidence: 99%

Minimizing Cost of Highway Maintenance Considering the Impact of Vehicle Emissions using an Artificial Bee Colony Approach

Semaan

Chien

Ting

2020

Transportation Research Record

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The increasing traffic demand has reduced the efficiency of road networks and intensified the maintenance need for mobility and safety, increasing vehicle emissions, reducing air quality, and affecting climate change. To mitigate the negative impacts of work zone activities, a reliable method that can optimize spatio-temporal work zone activities is desirable. Previous studies have aimed to minimize the total cost, including maintenance, user delay, and accident costs, yet the associated environmental impact has been neglected. This study aims to optimize work zone activities using the artificial bee colony (ABC) algorithm, considering the cost of vehicle emissions in addition to the aforementioned costs for an environmentally sustainable optimization. MOtor Vehicle Emission Simulator (MOVES) is applied to calculate emission rates. The results show that the ABC algorithm is very efficient to search for the optimal solution that yields the minimum cost taking into account the well-being of the environment.

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“…Three soft computing which are widely used are artificial neural networks, fuzzy systems and genetic algorithms. Synergistic integration is needed to become a hybrid model [8,9]. There are several soft computing techniques, such as artificial neural networks, fuzzy systems, and genetic algorithms, which have been used in infrastructure management with varying degrees of success.…”

Section: Related Studymentioning

confidence: 99%

Fuzzy Logic Based Life Cycle Cost Analysis Model for Preventive Road Maintenance by Considering User Costs

Iskandar¹,

Hadiwardoyo²,

Sumabrata³

2020

International Journal of Engineering Research and Technology

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Road maintenance programs are an important requirement so that road performance remains stable. Life cycle cost analysis (LCCA) is one of the methods in the pavement management process. LCCA is used to support decision makers as a network level analysis tool. Many transportation agencies have used deterministic and probabilistic LCCA approaches. Decision makers use the probability method to evaluate investment risk using input variables, assumptions, or uncertain estimates. Data input is ambiguous and uncertain, so the use of soft computing applications can be used. This paper discusses the development of LCCA preventive maintenance tools for road pavement using soft computing techniques. Fuzzy logic-based algorithm presents LCCA for pavement preventive maintenance by considering user costs. Algorithm with a rule-based fuzzy logic system where users can define rules to reflect agency policies and strategies. This algorithm is part of a framework that can be proposed for the use of other soft computing techniques in handling preventive maintenance of roads

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An improved artificial bee colony algorithm for pavement resurfacing problem

Cited by 16 publications

References 14 publications

An Integrated Multi-Objectives Optimization Approach on Modelling Pavement Maintenance Strategies for Pavement Sustainability

An Integrated Multi-Objectives Optimization Approach on Modelling Pavement Maintenance Strategies for Pavement Sustainability

Minimizing Cost of Highway Maintenance Considering the Impact of Vehicle Emissions using an Artificial Bee Colony Approach

Fuzzy Logic Based Life Cycle Cost Analysis Model for Preventive Road Maintenance by Considering User Costs

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