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A new mathematical model and a heuristic algorithm for the tourist trip design problem under new constraints: a real-world application

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OPSEARCH 2023年第4期60卷 1703-1730页

作者： Yalcin, Gulcin Dinc Malta, Hilal Saylik, Seher Eskisehir Tech Univ Fac Engn Dept Ind Engn Iki Eylul Campus TR-26555 Eskisehir Turkiye

The tourist trip design problem (TTDP) is about to generate routes for tourists to maximize the points of interest (POIs) visited within specific time windows. In this study, new constraints: budget, weather and break are considered. First, the budget is required for entrance fees and the distance between two points where a taxi has to be used. Additionally, the expense of the break was taken into account. Then, the weather was considered for summer and for other seasons. On a summer day, tourists are likely to prefer visiting POIs, which are indoor areas, between specific times e.g. 11 a.m. to 3 p.m. to protect against the side effects of the sun. Furthermore, tourists need to take a break to relax during the trip. A mathematical model of the TTDP with these new constraints (TTDP-BWB) was developed. Then, a heuristic algorithm was developed with a new defined function that took the new constraints into account. The algorithm was codded using Android Studio and developed a mobile application for the case of Eskisehir in Turkiye. Problems are generated on the small and medium scale for the case of Eskisehir and used large-scale problems from published literature. The results of the algorithm were compared with the results of the mathematical model for the small scale problems. Additional, large-scale problems from literature were solved to see the performance of the heuristic algorithm. Computational results showed that the algorithm is promising.

关键词： Tourist trip design problem heuristic algorithm Time windows Mobile application Mixed-integer programming

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Optimization of Route Placement for Multibeam Line Bathymetry Based on Self-heuristic algorithm and Kalman Filtering

Optimization of Route Placement for Multibeam Line Bathymetr...

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2023 IEEE International Conference on Electrical, Automation and Computer Engineering, ICEACE 2023

作者： Chen, Siyuan Xu, Jiayi Dai, Shuo He, Ming Zhejiang Gongshang University Hangzhou China

ISBN: (纸本)9798350309614

With the advantages of high efficiency and high accuracy, multibeam line bathymetry has become the main means of detecting seabed topography at present. It also plays an important role in the process of renovating and correcting the old measurement data in the sea area. In the actual process of multibeam bathymetry, the survey vessel will form a number of strips, and each strip contains the topographic information of the corresponding area. Careful and comprehensive planning of the route of the survey ship is carried out so as to plan the strips formed by the survey ship. The efficiency and accuracy of the entire multibeam line sounding process can be greatly improved. This paper mainly studies the route planning of the survey ship under the actual situation of multibeam bathymetry. In order to find out the most efficient and accurate routes, this paper establishes a rasterized model of the sea area and provides a supporting self-heuristic solving algorithm. It is worth mentioning that the above models and algorithms are applicable to most of the sea areas with irregular seabed topography. Additionally, after planning the optimal route, the survey vessel will travel along the optimal route according to the guidance of GPS. Considering the systematic error and random error of GPS positioning, this paper provides a solution of error correction during traveling based on Kalman filter, which greatly improves the accuracy and robustness of the algorithm. Finally, this paper takes the area of 2°W-0.5°W and 50°N-50.8°N in the English Channel as an example, and gives an optimal multibeam line sounding and bathymetry route planning scheme based on the above model and algorithm. Overall, this study fills the gap in the field of multibeam bathymetry and provides a new way of thinking and a new scheme for cost compression, efficiency multiplication and accuracy improvement of multibeam bathymetry. © 2023 IEEE.

关键词： heuristic algorithm Kalman Filter Multibeam Line Bathymetry Optimization of Route Placement Rasterized Model of Sea Area

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Multi-Satellite Imaging Task Planning for Large Regional Coverage: A heuristic algorithm Based on Triple Grids Method

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REMOTE SENSING 2024年第1期16卷 194页

作者： Li, Feng Wan, Qiuhua Wen, Feifei Zou, Yongkui He, Qien Li, Da Zhong, Xing Garzelli, Andrea Chinese Acad Sci Changchun Inst Opt Fine Mech & Phys Changchun 130033 Peoples R China Univ Chinese Acad Sci Daheng Coll Beijing 100049 Peoples R China Chang Guang Satellite Technol Co Ltd Changchun 130102 Peoples R China Jilin Univ Sch Math Changchun 130012 Peoples R China

Over the past few decades, there has been a significant increase in the number of Earth observation satellites, and the area of ground targets requiring observation has also been expanding. To effectively utilize the capabilities of these satellites and capture larger areas of ground targets, it has become essential to plan imaging tasks for large regional coverage using multiple satellites. First, we establish a 0-1 integer programming model to accurately describe the problem and analyze the challenges associated with solving the model. Second, we propose a heuristic algorithm based on the triple grids method. This approach utilizes a generated grid to create fewer candidate strips, a calculation grid to determine the effective coverage area more accurately, and a refined grid to solve the issue of repeated coverage of strips. Furthermore, we employ an approximation algorithm to further improve the solutions obtained from the heuristic algorithm. By comparing the proposed method to the traditional greedy heuristic algorithm and three evolutionary algorithms, the results show that our method has better performance in terms of coverage and efficiency.

关键词： multi-satellite large regional coverage heuristic algorithm triple grids method approximation algorithm

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A heuristic algorithm for Deploying Electric Taxi Charging Stations to Enhance Service Quality

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APPLIED SCIENCES-BASEL 2024年第18期14卷 8536页

作者： Li, Lingjie Zhang, Yu Cheng, Cheng Du, Hao Liu, Shifu Tongji Univ Key Lab Rd & Traff Engn Minist Educ Shanghai 201804 Peoples R China China Transportat Inst Tongji 1239 Siping Rd Shanghai 200092 Peoples R China Shanghai Tongke Transportat Technol Co Ltd Shanghai 200092 Peoples R China

With the growing maturity of electric vehicles technology and the increase in environmental awareness, electric vehicles have emerged as a feasible way to reduce carbon emissions due to transportation. In response, numerous cities have adopted electric vehicles into taxi and bus fleets to increase their use. As the use of electric taxis increases, the strategic deployment of charging stations becomes crucial to ensuring taxi operations. This study aims to optimize the deployment of electric taxi charging stations, with a focus on improving service quality. A heuristic algorithm, Improved K-means iterated with Queuing Theory (IKQT), is proposed. To validate the algorithm, over 11,000 GPS tracking trajectory data from Shanghai Qiangsheng taxis in April 2018 were analyzed. The results of the study demonstrate that the IKQT algorithm can significantly increase the utilization rate of charging stations, enabling them to serve more electric taxis during peak hours and thereby improving overall service quality. Specifically, the total waiting time for all charging services was reduced by approximately 6%, while the total number of unserved taxis across all charging stations decreased by roughly 19%. These improvements underscore the novelty and practical value of the IKQT in the deployment of electric taxi charging stations.

关键词： electric taxi charging station deployment heuristic algorithm queuing theory

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Multi School Bus Routing Problem with Road Safety Factor via A heuristic algorithm 34

Multi School Bus Routing Problem with Road Safety Factor via...

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34th Chinese Control and Decision Conference (CCDC)

作者： Liang Botian Liu Xinglu Kin, Chan Wai Tsinghua Univ Tsinghua Shenzhen Int Grad Sch Shenzhen 5180000 Peoples R China

ISBN: (纸本)9781665478960

In this paper, a heuristic algorithm is used to consider the multi-school bus route planning problem with road safety factor. According to the requirements of school bus route planning, constraints such as school bus capacity, station capacity, and maximum operating time are considered, and the safety factor of the road is integrated. Finally, the safest and optimal path scheme is obtained through the corresponding algorithm. This paper proposes the construction method of road safety index, applies it to specific cases, and proposes a corresponding heuristic algorithm in order to solve the problem. Finally, numerical examples are used to illustrate the effectiveness and superiority of the proposed method.

关键词： Multi school bus routing problem SBRP VRP Safety factor heuristic algorithm

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High speed ghost imaging based on a heuristic algorithm and deep learning

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Chinese Physics B 2021年第6期30卷 287-293页

作者： Yi-Yi Huang Chen Ou-Yang Ke Fang Yu-Feng Dong Jie Zhang Li-Ming Chen Ling-An Wu Institute of Physics Chinese Academy of SciencesBeijing 100190China University of Chinese Academy of Sciences Beijing 100049China IFSA Collaborative Innovation Center and School of Physics and Astronomy Shanghai Jiao Tong UniversityShanghai 200240China College of Engineering Physics Shenzhen Technology UniversityShenzhen 518118China

We report an overlapping sampling scheme to accelerate computational ghost imaging for imaging moving targets,based on reordering a set of Hadamard modulation matrices by means of a heuristic algorithm. The new condensed overlapped matrices are then designed to shorten and optimize encoding of the overlapped patterns, which are shown to be much superior to the random matrices. In addition, we apply deep learning to image the target, and use the signal acquired by the bucket detector and corresponding real image to train the neural network. Detailed comparisons show that our new method can improve the imaging speed by as much as an order of magnitude, and improve the image quality as well.

关键词： high speed computational ghost imaging heuristic algorithm deep learning

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Novel heuristic algorithm incorporating dynamic penalty and adaptive evolution strategy for heat integration network design

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JOURNAL OF CLEANER PRODUCTION 2024年 468卷

作者： Duan, Huanhuan Yu, Shangfan Gao, Xinglong Xiao, Yuan Cui, Guomin Univ Shanghai Sci & Technol Sch Energy & Power Engn Shanghai 200093 Peoples R China Henan Univ Anim Husb & Econ Sch Energy & Intelligence Engn Zhengzhou 450000 Peoples R China Zhengzhou Urban Planning Design & Survey Res Inst Zhengzhou 450000 Peoples R China

Designing efficient heat-exchanger networks is essential for the effective use of energy in the process industries, fostering sustainable and low-carbon development. Traditional heuristic algorithms often fail to balance global and local search processes adequately when solving heat exchanger network synthesis. This frequently leads to early structural fixation and limits the exploration of integer variable search spaces. This study presents an innovative structural enhancement approach, incorporating a dynamic penalty for utility operating costs and an adaptive evolution strategy. The developed method increases the number of heat exchangers by dynamically penalizing utility operating costs and allows evolutionary parameters to be adaptively adjusted based on historical solutions. This approach diminishes the dependence on manual parameter tuning while enhancing flow matching diversity. Moreover, novel metrics for assessing structural diversity, based on node-based nonstructural model with stream splitting are established to facilitate the transition between various optimization paths, thereby improving the algorithm's robustness throughout different stages of the optimization process. Finally, computational analysis on five industrial-scale cases yields more optimal solutions with varied structural configurations compared to previous studies, demonstrating the method's feasibility and effectiveness.

关键词： Heat -exchanger networks Structural evolution Dynamic penalty heuristic algorithm Adaptive evolution

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Developing a new heuristic algorithm for efficient reliability optimization

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International Journal of Information Technology (Singapore) 2022年第5期14卷 2505-2511页

作者： Garg, Deepika Dahiya, Tripti Shrivastava, Avinash K. GD Goenka University Haryana Gurugram India International Management Institute West Bengal Kolkata India

Due to massive globalisation across the world, a rampant industrialisation has been witnessed which has led to the usage of complex machinery in the industries. Desired output is generated when components of the system are in close synchronization with each other. Reliability optimization is one of the major parameter to determine the performance of a complex system under various limitations like cost, time, volume, etc. In this paper, a new heuristic algorithm has been developed to attain requisite reliability while solving constrained redundancy reliability optimization problem for complex systems using the sets of minimal paths. The proposed heuristic algorithm is applied to a problem of five unit system with linear constraints. Comparative analysis of the proposed heuristic algorithm with existing heuristic algorithms is done to observe the effectiveness of new heuristic algorithm vis-à-vis other existing algorithms and it is perceived that the proposed heuristic algorithm is providing finer results with respect to system reliability and computational efforts. © 2022, The Author(s), under exclusive licence to Bharati Vidyapeeth's Institute of Computer Applications and Management.

关键词： Complex network heuristic algorithm Minimal path sets Redundancy allocation

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An efficient optimization method for transcendental eigenvalue problems based on mode count constraints and heuristic algorithm

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STRUCTURAL AND MULTIDISCIPLINARY OPTIMIZATION 2024年第6期67卷 94-94页

作者： Liu, Xiang Song, Meijia Cent South Univ Sch Traff & Transportat Engn Key Lab Traff Safety Track Minist Educ Changsha 410075 Hunan Peoples R China Cent South Univ Joint Int Res Lab Key Technol Rail Traff Safety Changsha 410075 Hunan Peoples R China Cent South Univ Natl & Local Joint Engn Res Ctr Safety Technol Rai Changsha 410075 Hunan Peoples R China

An efficient, robust, and versatile optimization method (DSM-MCC-HA) is proposed for transcendental eigenvalue problems by combing the advantages of the dynamic stiffness method (DSM), mode count constraint (MCC), and heuristic algorithm (HA). The DSM is used to model free vibration, or buckling or wave propagation eigen problems exactly with very few DoFs leading to efficient computation;moreover, material and geometry are parameters in the analytical DSM models. The monotonically increasing integer-valued mode count based on the Wittrick-Williams algorithm is directly used as the constraint, and there is no need to compute the eigenvalues through dichotomy, which significantly reduces the computational time and meanwhile guarantees the robustness. heuristic algorithms are adopted as the optimization algorithm resulting in global optima, where the differentiability of the mode count constraint is not required. The proposed method is sufficient general to be applied to different eigenvalue optimization problems, such as lightweight optimization with eigenvalue constraints, band gap constraints or specified eigenvalue(s), maximization of eigenvalue or band gaps with mass constraint, etc.. Difficulties of repeated frequencies, localized modes, and eigenmode switching are not involved. Beam (plane frame) and plate (corrugated sandwich panel) built-up structures are adopted as examples to demonstrate the efficiency, robustness, and versatility of the proposed method.

关键词： Structure optimization Mode count constraint Dynamic stiffness method Transcendental eigenvalue problem heuristic algorithm

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Determining r- and ( r , s )-robustness of multiagent networks based on heuristic algorithm

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NEUROCOMPUTING 2024年 598卷

作者： Jiang, Jie Wu, Yiming Zhang, Zhaoming Zheng, Ning Meng, Wei Hangzhou Dianzi Univ Sch Cyberspace Hangzhou 310018 Peoples R China Guangdong Univ Technol Sch Automat Guangzhou 510006 Peoples R China

The graph properties of r - and ( r, s ) -robustness are of importance for multiagent networks since these properties ensure consensus among agents even in the presence of a limited number of arbitrarily misbehaving agents, given sufficiently large values for the integers r and s . However, determining the exact solutions of r - and ( r, s ) - robustness of an arbitrary directed graph has been proven to be computationally complex NP -hard problem. In this paper, we introduce a novel method, named the Determining Robustness based Genetic algorithm (DRSGA), for approximately calculating the r - and ( r, s ) -robustness using heuristic algorithm. According to graph theory in mathematical analysis, we first formalize the method for calculating the r - and ( r, s ) - robustness in directed graphs by utilizing a three -vertex set partition. Then, we transform these methods into a minimization problem of an n -dimensional discrete function and employ DRSGA to obtain an approximate solution. Finally, we validate the efficacy of our algorithm through a series of experiments compared to existing mixed -integer programming algorithms.

关键词： Multiagent networks Directed graphs Cyber security Network robustness heuristic algorithm

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