Bee Inspired Novel Optimization Algorithm and Mathematical Model for Effective and Efficient Route Planning in Railway System

Leong, Kah Huo; Abdul‐Rahman, Hamzah; Chen, Wang; Onn, Chiu Chuen; Loo, Siaw Chuing

doi:10.1371/journal.pone.0166064

Cited by 10 publications

(4 citation statements)

References 20 publications

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“…Taking all factors into account is currently very demanding due to the manual processing of circuits and shifts with some support from the KASO program. At present, the creation of circuits and shifts depends on the knowhow of employees and their many years of experience, because the KASO program does not design either circulation or shifts but is an excellent control tool [42,43].…”

Section: Resultsmentioning

confidence: 99%

Information System and Technology Optimization as a Tool for Ensuring the Competitiveness of a Railway Undertaking—Case Study

2020

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Information and communication technologies are becoming an increasingly important part of everyday life, as they facilitate many activities, mainly in the world of work, but also in scientific research and education. At present, informatics is one of the fastest growing sectors of the national economy. This development has had a significant impact on improving the quality of transport and transportation processes. The article is focused on the railway transport. It deals with the possibilities of planning the shifts of the train personnel and circulation of the vehicles. It describes the background of the topic. The scientific acquittance lies on the methodology proposed by authors. It presents a new idea of creating the shifts and circulations while being based on the current state and mathematical methods.

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Section: Resultsmentioning

confidence: 99%

Information System and Technology Optimization as a Tool for Ensuring the Competitiveness of a Railway Undertaking—Case Study

2020

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“…In his work [ 13 ] proposed a biological inspired bee system to optimize the routing in Railway systems. They conclude that the average solution results are better or equivalent than the traditional SA and GA methods.…”

Section: Literature Reviewmentioning

confidence: 99%

Information theory inspired optimization algorithm for efficient service orchestration in distributed systems

Lima

2021

PLoS ONE

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Distributed Systems architectures are becoming the standard computational model for processing and transportation of information, especially for Cloud Computing environments. The increase in demand for application processing and data management from enterprise and end-user workloads continues to move from a single-node client-server architecture to a distributed multitier design where data processing and transmission are segregated. Software development must considerer the orchestration required to provision its core components in order to deploy the services efficiently in many independent, loosely coupled—physically and virtually interconnected—data centers spread geographically, across the globe. This network routing challenge can be modeled as a variation of the Travelling Salesman Problem (TSP). This paper proposes a new optimization algorithm for optimum route selection using Algorithmic Information Theory. The Kelly criterion for a Shannon-Bernoulli process is used to generate a reliable quantitative algorithm to find a near optimal solution tour. The algorithm is then verified by comparing the results with benchmark heuristic solutions in 3 test cases. A statistical analysis is designed to measure the significance of the results between the algorithms and the entropy function can be derived from the distribution. The tested results shown an improvement in the solution quality by producing routes with smaller length and time requirements. The quality of the results proves the flexibility of the proposed algorithm for problems with different complexities without relying in nature-inspired models such as Genetic Algorithms, Ant Colony, Cross Entropy, Neural Networks, 2opt and Simulated Annealing. The proposed algorithm can be used by applications to deploy services across large cluster of nodes by making better decision in the route design. The findings in this paper unifies critical areas in Computer Science, Mathematics and Statistics that many researchers have not explored and provided a new interpretation that advances the understanding of the role of entropy in decision problems encoded in Turing Machines.

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“…These mass transportation systems contribute to solving the problem of connecting people with different parts of a city, especially in densely populated urban areas, allowing them to carry out the diverse activities that keep a city functioning [2][3][4]. Under optimal conditions, metro systems can move large numbers of people in a fast and efficient way, with lower transportation costs and coping with trafficrelated air pollution [5][6][7]. Thereby metro systems have become a crucial element in the development of cities not only in terms of economical benefits but also in terms of social and environmental impact.…”

Section: Introductionmentioning

confidence: 99%

Evolution of transport under cumulative damage in metro systems

Eraso-Hernandez¹,

Riascos²,

Michelitsch³

et al. 2021

Preprint

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Bee Inspired Novel Optimization Algorithm and Mathematical Model for Effective and Efficient Route Planning in Railway System

Cited by 10 publications

References 20 publications

Information System and Technology Optimization as a Tool for Ensuring the Competitiveness of a Railway Undertaking—Case Study

Information System and Technology Optimization as a Tool for Ensuring the Competitiveness of a Railway Undertaking—Case Study

Information theory inspired optimization algorithm for efficient service orchestration in distributed systems

Evolution of transport under cumulative damage in metro systems

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