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A Genetic Algorithm To Minimise Number Of Vehicles In An Electric Vehicle Routing Problem, Kiian Leong Bertran Queck, Hoong Chuin Lau
A Genetic Algorithm To Minimise Number Of Vehicles In An Electric Vehicle Routing Problem, Kiian Leong Bertran Queck, Hoong Chuin Lau
Research Collection School Of Computing and Information Systems
Electric Vehicles (EVs) and charging infrastructure are starting to become commonplace in major cities around the world. For logistics providers to adopt an EV fleet, there are many factors up for consideration, such as route planning for EVs with limited travel range as well as long-term planning of fleet size. In this paper, we present a genetic algorithm to perform route planning that minimises the number of vehicles required. Specifically, we discuss the challenges on the violations of constraints in the EV routing problem (EVRP) arising from applying genetic algorithm operators. To overcome the challenges, techniques specific to addressing the …
Route Planning For A Fleet Of Electric Vehicles With Waiting Times At Charging Stations, Baoxiang Li, Shashi Shekhar Jha, Hoong Chuin Lau
Route Planning For A Fleet Of Electric Vehicles With Waiting Times At Charging Stations, Baoxiang Li, Shashi Shekhar Jha, Hoong Chuin Lau
Research Collection School Of Computing and Information Systems
Electric Vehicles (EVs) are the next wave of technology in the transportation industry. EVs are increasingly becoming common for personal transport and pushing the boundaries to become the mainstream mode of transportation. Use of such EVs in logistic fleets for delivering customer goods is not far from becoming reality. However, managing such fleet of EVs bring new challenges in terms of battery capacities and charging infrastructure for efficient route planning. Researchers have addressed such issues considering different aspects of the EVs such as linear battery charging/discharging rate, fixed travel times, etc. In this paper, we address the issue of waiting …
Qos Routing Optimization Strategy Using Genetic Algorithm In Optical Fiber Communication Networks, Zhaoxia Wang, Zengqiang Chen, Zhuzhi Yuan
Qos Routing Optimization Strategy Using Genetic Algorithm In Optical Fiber Communication Networks, Zhaoxia Wang, Zengqiang Chen, Zhuzhi Yuan
Research Collection School Of Computing and Information Systems
This paper describes the routing problems in optical fiber networks, defines five constraints, induces and simplifies the evaluation function and fitness function, and proposes a routing approach based on the genetic algorithm, which includes an operator [OMO] to solve the QoS routing problem in optical fiber communication networks. The simulation results show that the proposed routing method by using this optimal maintain operator genetic algorithm (OMOGA) is superior to the common genetic algorithms (CGA). It not only is robust and efficient but also converges quickly and can be carried out simply, that makes it better than other complicated GA.