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An accelerated discrete artificial bee colony algorithm under the makespan constraint: Solving the distributed blocking flow shop scheduling problem with balanced energy consumption costs

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EXPERT SYSTEMS WITH APPLICATIONS 2025年 260卷

作者： Zhang, Chenyao Han, Yuyan Wang, Yuting Li, Junqing Gao, Kaizhou Liaocheng Univ Sch Comp Sci Liaocheng 252059 Peoples R China Shandong Normal Univ Sch Comp Sci Jinan 252000 Peoples R China Macau Univ Sci & Technol Macau Inst Syst Engn Taipa 999078 Macao Peoples R China

In the path of coordinating regional development, if different enterprises cannot coordinate and progress together, it will inevitably lead to the phenomenon of "bad money drives out good money". Therefore, this research addresses a distributed blocking flow shop scheduling problem with sequence-dependent setup time and aims to balance the energy consumption costs among factories while satisfying the makespan upper-bound criterion. This optimization problem is denoted as DFm|block,st(sd)|epsilon(ECC/C-max). We propose an accelerated discrete artificial bee colony (A-DABC) algorithm to address our established mathematical model. In the A-DABC algorithm, various advanced neighborhood operators are integrated to achieve a relative balance in the cost of energy consumption among distributed factories. To address the computational cost associated with the designed operators, we developed three accelerated evaluation mechanisms by integrating the energy cost adjustments resulting from insertions or swaps into the original energy cost, effectively reducing the overall computational complexity. The comprehensive statistical experiments demonstrate that the computational effort of energy consumption costs is significantly decreased, and A-DABC has prominent advantages in addressing DFm|block,st(sd)|epsilon(ECC/C-max) by comparing to four existing algorithms in all test cases.

关键词： Distributed flow shop Blocking Energy consumption cost discrete artificial bee colony algorithm Accelerated evaluation

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Optimization of task assignment for multi-farm multi-weeding robots based on discrete artificial bee colony algorithm

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EXPERT SYSTEMS WITH APPLICATIONS 2025年 267卷

作者： Chen, Jiong-Yu Pan, Quan-Ke Neufeld, Janis S. Miao, Zhong-Hua Shanghai Univ Sch Mechatron Engn & Automat Shanghai 200444 Peoples R China Liaocheng Univ Sch Comp Sci & Technol Liaocheng 252000 Peoples R China Otto von Guericke Univ Chair Operat Management D-39106 Magdeburg Germany

As smart agriculture continues to advance, the potential of agricultural robots to enhance productivity and lower costs becomes increasingly evident. This paper investigates the multi-farm multi-weeding robot task assignment problem (MFMWRTA) with minimization of the maximum completion time. A multi-farm discrete artificial bee colony (MFDABC) algorithm based on the improved discrete artificial bee colony (DABC) algorithm is presented to address this problem. The algorithm first generates high-quality initial solutions using the proposed multi-farm NEH (MFNEH) based heuristic and iterative greedy (IG) based heuristic, then assigns an appropriate number of weeding robots to each farm. During the employed bee and scout bee phases, this study develops five local search operators to enhance the algorithm's ability to perform local searches. During the onlooker bee phase, integrating the tournament selection strategy with the key robot concept assists the algorithm in escaping local optima. Experimental results show that the MFDABC algorithm outperforms existing heuristics on several test instances with better optimization performance and robustness.

关键词： Scheduling Agricultural robots Task assignment and scheduling Heuristics Multi-farm discrete artificial bee colony algorithm

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An efficient discrete artificial bee colony algorithm with dynamic calculation method for solving the AGV scheduling problem of delivery and pickup

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COMPLEX & INTELLIGENT SYSTEMS 2024年第1期10卷 37-57页

作者： Zhang, Xujin Sang, Hongyan Li, Zhongkai Zhang, Biao Meng, Leilei Liaocheng Univ Sch Comp Sci Liaocheng 252059 Shandong Peoples R China

To meet the production demand of workshop, this paper proposes an efficient discrete artificial bee colony (DABC) algorithm to solve a new automatic guided vehicle (AGV) scheduling problem with delivery and pickup in a matrix manufacturing workshop. The goal is to produce a AGV transportation solution that minimizes the total cost, including travel cost, time cost, and AGV cost. Therefore, a mixed integer linear programming model is established. To improve the transportation efficiency, a dynamic calculation method is developed. In the DABC algorithm, a heuristic algorithm and a median based probability selection method are used. For improving the quality of the solutions, four effective neighborhood operators are introduced. In the local search, a rule is given to save the operation time and a problem-based search operator is proposed to improve the quality of the best individual. Finally, a series of comparison experiments were implemented with the iterative greedy algorithm, artificial bee colony algorithm, hybrid fruit fly optimization algorithm, discrete artificial bee colony algorithm, improved harmony search, and hybrid genetic-sweep algorithm. The results show that the proposed DABC algorithm has high performance on solving the delivery and pickup problem.

关键词： Automatic guided vehicle Scheduling discrete artificial bee colony algorithm Matrix manufacturing workshop

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A discrete artificial bee colony algorithm for quadratic assignment problem

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JOURNAL OF HIGH SPEED NETWORKS 2022年第2期28卷 131-141页

作者： Peng, Zhong-yuan Huang, Yun-ji Zhong, Yu-bin Maoming Polytech Dept Social Sci Maoming Guangdong Peoples R China Guangzhou Univ Sch Math & Informat Sci Guangzhou Guangdong Peoples R China

The quadratic assignment problem (QAP) is a well-known challenging combinational optimization problem that has received many researchers' attention with varied real-world and industrial applications areas. Using the framework of basic artificial bee colony algorithm, frequently used crossover and mutation operators, and combined with an effective local search method, this paper proposes a simple but effective discrete artificial bee colony (DABC) algorithm for solving quadratic assignment problems (QAPs). Typical QAP benchmark instances are selected from QAPLIB in order to conduct the simulation experiment where common performance metrics are used to evaluate the algorithm. The paper also investigates the influence factors of the algorithm's performance. The results show that the proposed algorithm is a quite effective and practical new approach for handling QAP problems.

关键词： discrete artificial bee colony algorithm combinatorial optimization Quadratic Assignment Problem

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FIELD TRAVERSAL PATH PLANNING FOR AGRICULTURAL ROBOTS IN HILLY AREAS BASED ON discrete artificial bee colony algorithm

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INMATEH-AGRICULTURAL ENGINEERING 2024年第1期72卷 480-491页

作者： Lou, Xiaodong Li, Zheng Zhejiang Business Technol Inst Coll Digital Commerce Ningbo Zhejiang Peoples R China Shaoxing Univ Sch Teacher Educ Shaoxing Zhejiang Peoples R China

In this study, the discrete artificial bee colony (DABC) algorithm was proposed to plan the path of agricultural robots traversing multiple fields in hilly areas. Based on the basic ABC algorithm as the framework, the path coding method was adopted, and the discrete crossover operator, reverse operator, immune operator, and single/multi-step 2 -opt operator were comprehensively used to help hired bees, observing bees, and scout bees to generate new food sources. Finally, the optimized field traversal order and the entrance and exit distribution of each field were obtained. The simulation results showed that compared with the traditional ABC algorithm, the average shortest path of the DABC algorithm proposed in this study was shortened by 1.59%, accompanied by the less iterations contributing to algorithm convergence and good ability to jump out of the local optimal solution. The simulation experiment was carried out using real field data and field operation parameters. The field traversal order and the entrance and exit distribution obtained by the proposed method can effectively reduce the length of the transfer path and its repeatability. This study exhibits superiority and feasibility in the field traversal path planning of agricultural robots in hilly areas, and the trajectory coordinates output by the algorithm can provide a path reference for large -area operations of agricultural machinery drivers or unmanned agricultural machineries.

关键词： Hilly area agricultural robots traversal path planning 2-opt discrete artificial bee colony algorithm

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A slack speed-up based discrete artificial bee colony algorithm for resource-constrained operating room scheduling problem

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COMPUTERS & INDUSTRIAL ENGINEERING 2023年 186卷

作者： Yang, Mei-Chen Pan, Quan-Ke Sang, Hong-Yan Li, Wei-Min Wang, Yu-Long Shanghai Univ Sch Med Shanghai 200444 Peoples R China Shanghai Univ Sch Mech & Elect Engn & Automat Shanghai 200444 Peoples R China Liaocheng Univ Sch Comp Sci Liaocheng 252000 Peoples R China Shanghai Univ Sch Comp Engn & Sci Shanghai 200444 Peoples R China 99 Shangda Rd Shanghai Peoples R China

In today's world, with the rapidly increasing demand for health care and the scarcity of health care resources, it is very important to provide more services under limited conditions. This paper focuses on a resource-constrained operating room scheduling (RCORS) problem with the characteristic of multi-stage. First, a mixed integrated programming model is presented to uncover the impact of no-wait and resources on the problem. Second, a slack speed-up based discrete artificial bee colony (SDABC) algorithm is devised to tackle varying configurations effectively. The solution is represented as a one-dimensional list, from which a complete schedule is derived by a decoding heuristic. Additionally, a speed-up evaluation procedure based on a slack-resource model is developed. In SDABC, an initial population with high quality and diversity is generated based on a problem-specific heuristic. Different strategies are employed in the three stages of SDABC to balance the local optimal, population optimal, and global optimal. A variable neighborhood search is introduced to enhance local exploration capabilities. Finally, we conduct a large number of experiments to verify the performance of the proposed algorithm. Numerical analysis proves that SDABC has significant advantages for solving the RCORS problem.

关键词： Operating room scheduling Multi-resource Mixed integrated programming model discrete artificial bee colony algorithm Speed-up evaluation

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Repair Strategy of Military Communication Network Based on discrete artificial bee colony algorithm

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IEEE ACCESS 2020年 8卷 73051-73060页

作者： Chen, Guanyu Sun, Peng Zhang, Jieyong Air Force Engn Univ Coll Informat & Nav Xian 710077 Peoples R China Northwestern Polytech Univ Sch Comp Sci Xian 710077 Peoples R China

After the military communications network is attacked by the enemy, in order to ensure that the information flow in the command and control organization can continue to be transmitted smoothly, the damaged network topology needs to be repaired in a timely and effective manner. The problem of repairing military communication network under the circumstance of nodes are hit in the network is described. This paper propose a method to repair damaged network by adding edges to the damaged network topology, which aims at maximizing network invulnerability. Network topological connection cost is based on average connection degree. The repair model is established with the consideration of connect cost limit and network connectivity. The model solving method based on discrete artificial bee colony algorithm is designed. Finally, proposed repair method is tested and compared with other three edge addition repair methods with a specific case of network. The experimental results show that the proposed method could enhance damaged network & x2019;s invulnerability and outperforms the compared methods.

关键词： Maintenance engineering Organizations Time division multiplexing Task analysis Network topology Military communication Communication networks Command and control system repair model repair strategy edge addition discrete artificial bee colony algorithm information flow

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An Effective discrete artificial bee colony algorithm for Scheduling an Automatic-Guided-Vehicle in a Linear Manufacturing Workshop

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IEEE ACCESS 2020年 8卷 35063-35076页

作者： Zou, Wen-Qiang Pan, Quan-Ke Tasgetiren, M. Fatih Shanghai Univ Sch Mechatron Engn & Automat Shanghai 200072 Peoples R China Liaocheng Univ Sch Comp Sci Liaocheng 252000 Shandong Peoples R China Yasar Univ Int Logist Management Dept TR-35100 Izmir Turkey

This paper deals with a new automatic guided vehicle (AGV) scheduling problem from the material handling process in a linear manufacturing workshop. The problem is to determine a sequence of Cells for AGV to travel to minimize the standard deviation of the waiting time of the Cells and the total travel distance of AGV. For this purpose, we first propose an integer linear programming model based on a comprehensive investigation. Then, we present an improved nearest-neighbor-based heuristic so as to fast generate a good solution in view of the problem-specific characteristics. Next, we propose an effective discrete artificial bee colony algorithm with some novel and advanced techniques including a heuristic-based initialization, six neighborhood structures and a new evolution strategy in the onlooker bee phase. Finally, the proposed algorithms are empirically evaluated based on several typical instances from the real-world linear manufacturing workshop. A comprehensive and thorough experiment shows that the presented algorithm produces superior results which are also demonstrated to be statistically significant than the existing algorithms.

关键词： Automated guided vehicle heuristic discrete artificial bee colony algorithm scheduling linear manufacturing workshop

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Mathematical modeling and a discrete artificial bee colony algorithm for the welding shop scheduling problem

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MEMETIC COMPUTING 2019年第4期11卷 371-389页

作者： Li, Xinyu Xiao, Shengqiang Wang, Cuiyu Yi, Jin Huazhong Univ Sci & Technol State Key Lab Digital Mfg Equipment & Technol Sch Mech Sci & Engn Wuhan 430074 Peoples R China Natl Univ Singapore Dept Ind Syst Engn & Management Singapore Singapore

The welding process which is one of the most important assembly processes is widespread in the modern manufacturing industry, including aerospace, automotive and engineering machinery. The welding shop scheduling greatly impacts the efficiency of whole production system. However, few studies on the welding shop scheduling problem (WSSP) were reported. In this paper, a mathematical model and an improved discrete artificial bee colony algorithm (DABC) are proposed for the WSSP. Firstly, it is defined where multi-machine can process one job at the same time in the WSSP. Secondly, the mathematical models of WSSP have been constructed. Thirdly, an effective DABC is proposed to solve the WSSP, considering job permutation and machine allocation simultaneously. To improve the performance of proposed DABC algorithm, the effective operators have been designed. Three instances with different scales are used to evaluate the effectiveness of proposed algorithm. The comparisons with other two algorithms including genetic algorithm and grey wolf optimizer are also provided. Experimental results show that the proposed model and algorithm achieve good performance. Finally, the proposed model and DABC algorithm are applied in a real-world girder welding shop from a crane company in China. The results show that proposed model and algorithm reduces 55.17% production time comparing with the traditional algorithm and the scheduled machine allocation provides more reasonable arrangements for workers and machine loads.

关键词： Welding Scheduling discrete artificial bee colony algorithm Welding shop scheduling

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An effective discrete artificial bee colony algorithm for multi-AGVs dispatching problem in a matrix manufacturing workshop

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EXPERT SYSTEMS WITH APPLICATIONS 2020年 161卷 113675-113675页

作者： Zou, Wen-Qiang Pan, Quan-Ke Meng, Tao Gao, Liang Wang, Yu-Long Shanghai Univ Sch Mechatron Engn & Automat Shanghai 200072 Peoples R China Liaocheng Univ Sch Math Sci Liaocheng 252000 Shandong Peoples R China Huazhong Univ Sci & Technol State Key Lab Digital Mfg Equipment & Technol Wuhan Peoples R China Liaocheng Univ Sch Comp Sci Liaocheng 252000 Shandong Peoples R China

This paper addresses a new multiple automatic guided vehicle dispatching problem (AGVDP) from material handling process in a matrix manufacturing workshop. The problem aims to determine a solution with the objective of minimizing the transportation cost including travel cost, penalty cost for violating time and AGV cost. For this purpose, a mixed integer linear programming model is first formulated based on a comprehensive investigation. Then, a discrete artificial bee colony algorithm (DABC) is presented together with some novel and advanced techniques for solving the problem. In the proposed DABC algorithm, a nearest-neighbor-based heuristic based on the problem-specific characteristics is presented to generate an initial solution with a high level of quality. Five effective neighborhood operators are presented to generated neighboring solutions with a high level of diversity. Four theorems are proposed to avoid the unfeasible solutions generated by the neighborhood operators. Two new control parameters are introduced. One is to balance the global exploration and local exploitation in employed bee and onlooker bee phases. The other is to enhance the local exploitation capability of the neighborhood operators. Besides, an insertion-based local search method is provided for the scout bee phase to lead the algorithm to a promising region of the solution space. A comprehensive and thorough evaluation with 110 instances collected from a real-world factory shows that the presented algorithm produces superior results which are also demonstrated to be statistically significant than the existing algorithms in the close related literature. (c) 2020 Elsevier Ltd. All rights reserved.

关键词： Automated guided vehicle Dispatching Heuristics Matrix manufacturing workshop discrete artificial bee colony algorithm

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