A Hyper-Heuristic Algorithm for Time-Dependent Green Location Routing Problem With Time Windows

Zhang, Chunmiao; Zhao, Yanwei; Leng, Longlong

doi:10.1109/access.2020.2991411

Cited by 18 publications

(13 citation statements)

References 43 publications

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“…A hyper-heuristic algorithm (HH) that consists of two levels, high-level heuristics, and low-level heuristics, is proposed to solve the time-dependent green location routing problem with time windows (TDLGRP) [66]. The study objective is to minimize costs, including opened depot costs, enabled vehicle costs, and fuel consumption costs.…”

Section: ) Hyper-heuristicsmentioning

confidence: 99%

Problem Solving in Crowd Management Using Heuristic Approach

et al. 2022

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There are many problems that procedural algorithms can solve efficiently. However, these algorithms are sometimes too slow to abide by the time available for performing the solution; other times, it is impossible to get a solution using procedural algorithms. A heuristic method is a practical approach that can reach an approximation of an efficient solution where the optimum is not guaranteed. Heuristic techniques are applied in many real-world problems, including crowd management; using heuristic-based models helped to comprehend crowd behavior better and increase simulation reliability. This paper reviews many heuristic-related articles to gather the aspects of the topic in one place and clear the fuzziness to make it easy to comprehend. The paper covers some of the previous works with similar approaches and presents state-of-the-art heuristic solutions for real-world problems. These techniques are discussed under three classifications: simple heuristics, meta-heuristics, and hyper-heuristics. Most importantly, the paper explores the heuristic role in crowd field problems concluding that heuristics are primarily applied in modeling when it comes to the Crowd field. It investigates different heuristics for crowd management. The main intent of this review is to establish a comprehensive understanding of heuristics-related operations in the crowd management field. Moreover, it aims to support other researchers' future work and fill research gaps by highlighting the absence of crowd problems from heuristics literature and the limitations of each heuristics approach.

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Section: ) Hyper-heuristicsmentioning

confidence: 99%

Problem Solving in Crowd Management Using Heuristic Approach

et al. 2022

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“…Constraint (10) avoids the formation of subloops between various customer points. Constraint (11) ensures that each vehicle can only exit from one distribution center at most. Constraint (12) ensures that each customer point must have one and only one vehicle service.…”

Section: Optimization Modelmentioning

confidence: 99%

“…Zhang et al designed a time-dependent green location path problem model with time windows. e model minimizes costs, including the cost of opening warehouses, the cost of starting vehicles, and the cost of fuel consumption [11]. However, the above research does not consider the security problem.…”

Section: Introductionmentioning

confidence: 99%

Logistics Distribution Location Algorithm Based on Improved Imperial Competition Algorithm

2021

Scientific Programming

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To solve the problems of warehouse explosion and delay of logistics distribution network under the sudden explosion of demand on “double 11” and “618,” this paper proposes a logistics distribution network location algorithm that can consider reliability, green environmental protection, and path optimization. Firstly, the transportation model of logistics distribution network location-route optimization is established. Under the condition that the transportation model satisfies the vehicle path reliability constraint, it can minimize the total cost, including logistics distribution cost, transportation oil consumption, and CO2 emission cost. This paper designs an improved imperial competition algorithm to solve it according to the characteristics of the transportation model. Firstly, the competition mechanism of “United Lian Heng” was introduced in the initial national stage, enhancing the information exchange and retaining the superior population. Secondly, in the process of empire assimilation, we can learn from the colonial rule strategy, which is gradually infiltrated and assimilated by all levels of the country to enhance the development ability of the algorithm. Finally, the algorithm designs a mechanism to judge and jump out of local optimum, so as to avoid “premature” affecting the optimization performance. The rationality of the model and the effectiveness of the improved imperial competition algorithm are verified by simulation experiments of different scales, while the influence of reliability level is analyzed. Experimental results show that the proposed method can effectively solve problems of different scales and maintain stable performance under different reliability levels. Moreover, its algorithm performance is better than that of the standard imperial competition algorithm.

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“…Moreover, using DWC technology, EV charging operation is accomplished while the EV is moving over the charging infrastructure. So it is essential to pay attention to both the location and routing problems in systems based on wireless charging [29]. The location-routing problem (LRP) is a branch of locational analysis research that is distinguished by paying close attention to the underlying issues with vehicle routing.…”

Section: Introductionmentioning

confidence: 99%

Optimal Siting and Sizing of Wireless EV Charging Infrastructures Considering Traffic Network and Power Distribution System

et al. 2022

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The main challenges in the widespread deployment of electric vehicles (EVs) are limited driving range, long charging downtime, lack of charging stations in some areas, and high battery cost. Dynamic wireless charging (DWC) technology can overcome some of these obstacles by recharging EV batteries remotely while vehicles move over the charging infrastructures. However, most studies have limited this technology to public EVs working in specific routes like electric buses and taxis routes. This paper presents a long-term stochastic scenario-based mathematical model for allocating and sizing DWC infrastructures considering Ev's location-routing, power distribution system (PDS) losses, and transportation network traffic. The proposed long-term model allows all types of EVs to take advantage of the installed DWC infrastructures and facilitate EVs' widespread use by overcoming conventional charging technologies problems. The optimization problem is structured in the form of a Mixed Integer Non-Linear Programming (MINLP) model. Simulation results with detailed analyzes are furnished to illustrate the characteristics and performance of the model in a coupled network combining transportation and power networks. The numerical analysis provides meaningful insight into the transportation system design based on DWC technology and the effect of EV routing on the charging infrastructure allocation. Simulation results show that using Location-Routing Problem (LRP) can save up to 45% of the total cost of the DWC system. In addition, the proposed model, along with the simulations performed, demonstrates the advantage of DWC technology in reducing the size of vehicle batteries.

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A Hyper-Heuristic Algorithm for Time-Dependent Green Location Routing Problem With Time Windows

Cited by 18 publications

References 43 publications

Problem Solving in Crowd Management Using Heuristic Approach

Problem Solving in Crowd Management Using Heuristic Approach

Logistics Distribution Location Algorithm Based on Improved Imperial Competition Algorithm

Optimal Siting and Sizing of Wireless EV Charging Infrastructures Considering Traffic Network and Power Distribution System

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