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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 effective discrete artificial bee colony algorithm for flow shop scheduling problem with intermediate buffers

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Journal of Central South University 2015年第9期22卷 3471-3484页

作者：张素君顾幸生 School of Mechanical and Electrical Engineering Henan Institute of Science and Technology Key Laboratory of Advanced Control and Optimization for Chemical Process Ministry of Education East China University of Science and Technology

An effective discrete artificial bee colony(DABC) algorithm is proposed for the flow shop scheduling problem with intermediate buffers(IBFSP) in order to minimize the maximum completion time(i.e makespan). The effective combination of the insertion and swap operator is applied to producing neighborhood individual at the employed bee phase. The tournament selection is adopted to avoid falling into local optima, while, the optimized insert operator embeds in onlooker bee phase for further searching the neighborhood solution to enhance the local search ability of algorithm. The tournament selection with size 2 is again applied and a better selected solution will be performed destruction and construction of iterated greedy(IG) algorithm, and then the result replaces the worse one. Simulation results show that our algorithm has a better performance compared with the HDDE and CHS which were proposed recently. It provides the better known solutions for the makespan criterion to flow shop scheduling problem with limited buffers for the Car benchmark by Carlier and Rec benchmark by Reeves. The convergence curves show that the algorithm not only has faster convergence speed but also has better convergence value.

关键词： discrete artificial bee colony algorithm flow shop scheduling problem with intermediate buffers destruction and construction tournament selection

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A discrete artificial bee colony algorithm for the total flowtime minimization in permutation flow shops

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INFORMATION SCIENCES 2011年第16期181卷 3459-3475页

作者： Tasgetiren, M. Fatih Pan, Quan-Ke Suganthan, P. N. Chen, Angela H-L Liaocheng Univ Coll Comp Sci Liaocheng 252059 Peoples R China Yasar Univ Dept Ind Engn Izmir Turkey Nanyang Technol Univ Sch Elect & Elect Engn Singapore Singapore Nanya Inst Technol Dept Finance Tao Yuan 320 Taiwan

Obtaining an optimal solution for a permutation flowshop scheduling problem with the total flowtime criterion in a reasonable computational timeframe using traditional approaches and optimization tools has been a challenge. This paper presents a discrete artificial bee colony algorithm hybridized with a variant of iterated greedy algorithms to find the permutation that gives the smallest total flowtime. Iterated greedy algorithms are comprised of local search procedures based on insertion and swap neighborhood structures. In the same context, we also consider a discrete differential evolution algorithm from our previous work. The performance of the proposed algorithms is tested on the well-known benchmark suite of Taillard. The highly effective performance of the discrete artificial bee colony and hybrid differential evolution algorithms is compared against the best performing algorithms from the existing literature in terms of both solution quality and CPU times. Ultimately, 44 out of the 90 best known solutions provided very recently by the best performing estimation of distribution and genetic local search algorithms are further improved by the proposed algorithms with short-term searches. The solutions known to be the best to date are reported for the benchmark suite of Taillard with long-term searches, as well. (C) 2011 Elsevier Inc. All rights reserved.

关键词： Permutation flowshop scheduling problem Iterated greedy algorithm discrete differential evolution algorithm discrete artificial bee colony algorithm Estimation of distribution algorithm Genetic local search

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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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Optimum tie switches allocation and DG placement based on maximisation of system loadability using discrete artificial bee colony algorithm

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IET GENERATION TRANSMISSION & DISTRIBUTION 2016年第10期10卷 2277-2284页

作者： Aman, Muhammad Mohsin Jasmon, Ghauth B. Mokhlis, Hazlee Abu Bakar, Ab Halim Univ Malaya Dept Elect Engn Kuala Lumpur 50603 Malaysia

Due to an exponential increase in load demand and lack of capital resources to improve the existing transmission line infrastructure, power utilities are focusing on methods to increase the efficiency and loadability of existing infrastructure. This study presents a new approach for simultaneous optimum distributed generation (DG) placement and optimum tie-switch allocation based on maximisation of system loadability using discrete artificial bee colony algorithm. The proposed algorithm is tested on 16-Bus, 33-Bus and 69-Bus radial distribution test system. The obtained results show that with simultaneous optimum DG placement and optimum tie-switch allocation, better results are achieved rather than solving two problems independently. Further it was also found that the proposed method has improved the efficiency of the system in terms of maximisation of system loadability, reduction in power system losses, improving the kVA margin to maximum loadability and voltage quality improvement.

关键词： distributed power generation power transmission lines power semiconductor switches power supply quality optimisation optimum tie switches allocation DG placement simultaneous optimum distributed generation placement system loadability maximisation discrete artificial bee colony algorithm load demand transmission line infrastructure improvement power utilities 16-bus radial distribution test system 33-bus radial distribution test system 69-bus radial distribution test system power system loss reduction voltage quality improvement

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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 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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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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