An investigation of nature inspired algorithms on a particular vehicle routing problem in the presence of shift assignment

Alp, Gözde; Alkaya, Ali Fuat

doi:10.1016/j.cor.2021.105685

Cited by 6 publications

(2 citation statements)

References 27 publications

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“…The inverted generational distance (IGD) and the hyper‐volume (HV) two evaluation indicators are introduced in this paper to evaluate the quality of the Pareto optimal solutions obtained by the multi‐objective HESA. Therein, the IGD indicator (Alp and Alkaya, 2022) is used to measure the convergence and the distribution performance of the obtained Pareto optimal solutions, and also the overall gap including the convergence degree and the diversity of two aspects between the obtained Pareto optimal solutions set and the reference Pareto optimal solutions set. The calculation equations of the IGD are given as follows:

\begin{equation}{\rm{IGD = }}\frac{1}{S}\sum_{i = 1}^S {{{\min }}_{j = \left\{ {1,2, \ldots ,Q} \right\}}d\left( {F_i^*,{F}_j} \right)} \end{equation}

…”

Section: Multi‐objective Hesamentioning

confidence: 99%

A multi‐objective hybrid evolutionary search algorithm for parallel production line balancing problem including disassembly and assembly tasks

Zhang

Li-xia

Chen

et al. 2022

Int Trans Operational Res

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This paper proposes a multi‐objective hybrid evolutionary search algorithm to simultaneously optimize the number of workstations, the idle index and the quantity of the production equipment required for the parallel production line balancing problem including disassembly and assembly tasks. The proposed algorithm uses the crossover operation and the mutation operation to generate neighborhood individuals of the current evolutionary population. Based on the mixed population composed of the current evolutionary population and the newly generated neighborhood population, a novel population update method is developed. The individuals of the new generation population are composed of Pareto dominant individuals filtered from the mixed population and several individuals randomly selected from the dominated individuals. Then the local search strategy based on simulated annealing operation is applied to the new generation of population individuals to overcome the defect of premature convergence of the proposed algorithm. By solving test examples of different scales and comparing them with a variety of classical algorithms, the advantages in the aspects of the diversity, the convergence, and the distribution of the solution results of the proposed algorithm are proved. Finally, the established mathematical model and the developed algorithm are applied to the parallel production line designed for the bogie remanufacturing production line of a railway freight car maintenance company. The advantages of the parallel production line in improving the production efficiency and reducing the production cost are identified.

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\begin{equation}{\rm{IGD = }}\frac{1}{S}\sum_{i = 1}^S {{{\min }}_{j = \left\{ {1,2, \ldots ,Q} \right\}}d\left( {F_i^*,{F}_j} \right)} \end{equation}

…”

Section: Multi‐objective Hesamentioning

confidence: 99%

A multi‐objective hybrid evolutionary search algorithm for parallel production line balancing problem including disassembly and assembly tasks

Zhang

Li-xia

Chen

et al. 2022

Int Trans Operational Res

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“…The goal of a unique vehicle-routing problem is to find cost-effective routes for a large number of vehicles [ 1 , 2 , 3 ]. Meanwhile, new issues have arisen, especially in traffic factors such as low data rates, energy efficiency, congestion, and the fastest route [ 4 , 5 , 6 ]. This study focuses on seeking the most effective and the shortest route from a source point to a destination point in urban areas.…”

Section: Introductionmentioning

confidence: 99%

Heterogeneous Algorithm for Efficient-Path Detection and Congestion Avoidance for a Vehicular-Management System

Melaouene

Razaque

Romadi

2023

Sensors

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Finding reliable and efficient routes is a persistent problem in megacities. To address this problem, several algorithms have been proposed. However, there are still areas of research that require attention. Many traffic-related problems can be resolved with the help of smart cities that incorporate the Internet of Vehicles (IoV). On the other hand, due to rapid increases in the population and automobiles, traffic congestion has become a serious concern. This paper presents a heterogeneous algorithm called ant-colony optimization with pheromone termite (ACO-PT), which combines two state-of-the-art algorithms, pheromone termite (PT) and ant-colony optimization (ACO), to address efficient routing to improve energy efficiency, increase throughput, and shorten end-to-end latency. The ACO-PT algorithm seeks to provide an effective shortest path from a source to a destination for drivers in urban areas. Vehicle congestion is a severe issue in urban areas. To address this issue, a congestion-avoidance module is added to handle potential overcrowding. Automatic vehicle detection has also been a challenging issue in vehicle management. To address this issue, an automatic-vehicle-detection (AVD) module is employed with ACO-PT. The effectiveness of the proposed ACO-PT algorithm is demonstrated experimentally using network simulator-3 (NS-3) and Simulation of Urban Mobility (SUMO). Our proposed algorithm is compared with three cutting-edge algorithms. The results demonstrate that the proposed ACO-PT algorithm is superior to earlier algorithms in terms of energy usage, end-to-end delay, and throughput.

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A Novel Framework for Multi-objective Optimization Problems

Alp¹,

Alkaya²

2023

Lecture Notes in Networks and Systems

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An investigation of nature inspired algorithms on a particular vehicle routing problem in the presence of shift assignment

Cited by 6 publications

References 27 publications

A multi‐objective hybrid evolutionary search algorithm for parallel production line balancing problem including disassembly and assembly tasks

A multi‐objective hybrid evolutionary search algorithm for parallel production line balancing problem including disassembly and assembly tasks

Heterogeneous Algorithm for Efficient-Path Detection and Congestion Avoidance for a Vehicular-Management System

A Novel Framework for Multi-objective Optimization Problems

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