One of the most applicable versions of the Vehicle Routing Problem (VRP) which has been widely studied in logistic services is Capacitated Vehicle Routing Problem (CVRP). There are many algorithms to solve the CVRP to minimize total travelled distance. Some of the most recent and efficient metaheuristic algorithms are capable of generating solutions within 0.5% to 1% gap from the optimum for instance problems adopted from the literature considering hundreds or thousands of demand points. In this contribution, a novel hybrid algorithm is proposed based on Gravitational Emulation Local Search (GELS) and Genetic Algorithm (GA). This algorithm alleviates the weaknesses of the GELS algorithm. The performance of the proposed algorithm, which is called GELSGA, is compared with other meta-heuristics. The obtained results show that the proposed algorithm can compete vigorously with them. In addition, the proposed algorithm could obtain solutions close to the Best Known Solutions (BKS) for many instance problems. © 2013 IEEE.

Arun Kumar S

Department of Information Security

School of Computer Science and Engineering

Vellore Campus

Rahmani Hosseinabadi A.A

Slowik A

Sadeghilalimi M

Farokhzad M

Babazadeh Shareh M

Fulltext

Vellore Institute of Technology (VIT) is a private university located in&nbsp;Tamil Nadu, India. Founded in 1984, as Vellore Engineering College, the institution offers 20 undergraduate, 34 postgraduate, four integrated and four research programs. It has campuses in Vellore, Amravati, Bhopal and Chennai.

VIT is one of the top ranked private universities in India according to NIRF, THE and QS Rankings.&nbsp;Govt. of India has recognized&nbsp;VIT, Vellore as an&nbsp;Institution of Eminence. This has allowed VIT to take independent quality initiatives and move up in world ranking.

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VIT University

An Ameliorative Hybrid Algorithm for Solving the Capacitated Vehicle Routing Problem

IEEE Access

The Internet of Things (IoT) is a distributed system that connects everything via internet. IoT infrastructure contains multiple resources and gateways. In such a system, the problem of optimizing IoT resource allocation and scheduling (IRAS) is vital, because resource allocation (RA) and scheduling deals with the mapping between recourses and gateways and is also responsible for optimally allocating resources to available gateways. In the IoT environment, a gateway may face hundreds of resources to connect. Therefore, manual resource allocation and scheduling is not possible. In this paper, the whale optimization algorithm (WOA) is used to solve the RA problem in IoT with the aim of optimal RA and reducing the total communication cost between resources and gateways. The proposed algorithm has been compared to the other existing algorithms. Results indicate the proper performance of the proposed algorithm. Based on various benchmarks, the proposed method, in terms of “total communication cost”, is better than other ones.

Sensors

IoT Resource Allocation and Optimization Based on Heuristic Algorithm

The urban waste collection problem and its disposal activities are among the most important municipal services involving many operational issues. In this paper, a mixed-integer linear programming (MILP) model was developed for the multi-trip Capacitated Arc Routing Problem (CARP) in order to minimize total cost. In the proposed model, depots and disposal facilities were located in different places. In order to validate the proposed model, several small-sized instances were solved by the CPLEX solver of GAMS software. Then, a hybrid algorithm using the Taguchi parameter design method was developed based on an improved Max-Min Ant System (IMMAS) to solve well-known test problems and large-sized instances. Computational results show high efficiency for the proposed algorithm. © 2018 Elsevier Ltd

Computers & Electrical Engineering

An improved ant colony optimization for the multi-trip Capacitated Arc Routing Problem

European Journal of Operational Research

The Capacitated Vehicle Routing Problem: Stronger bounds in pseudo-polynomial time

Neural Computing and Applications

OVRP_GELS: solving open vehicle routing problem using the gravitational emulation local search algorithm

Discrete Applied Mathematics

A matheuristic for the asymmetric capacitated vehicle routing problem

Applied Mathematical Modelling

A new efficient approach for solving the capacitated Vehicle Routing Problem using the Gravitational Emulation Local Search Algorithm

Journal	Data powered by TypesetIEEE Access
Publisher	Data powered by TypesetInstitute of Electrical and Electronics Engineers (IEEE)
ISSN	21693536
Open Access	Yes