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Maradbcm算法 1

三维布局；势能曲面变平；布局优化；性能约束 1

业务架构集成；业务组件；组件识别；CRUD矩阵；启发式 1

中断型协调器 1

人工智能 1

几何构造 1

动态规划 1

双库协同机制 1

启发型协调器 1

启发式 1

启发式搜索 1

多智能体；动态作战任务；任务组形成；启发式规则；组网开销 1

故障诊断 1

数值域划分算法 1

机器人导航 1

测试优化 1

知识发现 1

神经网络；初值问题（IVP）；函微分方程（FDE）；无监督学习；遗传算法（GAs）；内点技术（IPT） 1

移动机器人 1

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A job-insertion heuristic for minimizing the mean flowtime in dynamic flowshops

Guang GUO, Bo WU, Shuzi YANG

《机械工程前沿（英文）》 2011年第6卷第2期页码 197-202 doi: 10.1007/s11465-011-0211-5

摘要：

A new adaptive job-insertion based heuristic is presented to minimize the mean flowtime in a dynamic flowshop consisting of machines. Job orders arrive to the system randomly, and the job arrival or release dates are not known in advance. The heuristic is derived by inserting new jobs into the scheduled sequence as needed when the machine becomes free. Computation results indicate that the proposed heuristic performs 2.7%–10.8% better than the SPT dispatching rule, which is currently one of the most effective methods for minimizing the mean flowtime in dynamic flowshops.

关键词： scheduling dynamic flowshops flowtime heuristic mean flowtime

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Enterprise-wide optimization of integrated planning and scheduling for refinery-petrochemical complex with heuristic

《化学科学与工程前沿（英文）》 2023年第17卷第10期页码 1516-1532 doi: 10.1007/s11705-022-2283-7

摘要： This paper focuses on the integrated problem of long-term planning and short-term scheduling in a large-scale refinery-petrochemical complex, and considers the overall manufacturing process from the upstream refinery to the downstream petrochemical site. Different time scales are incorporated from the planning and scheduling subproblems. At the end of each discrete time period, additional constraints are imposed to ensure material balance between different time scales. Discrete time representation is applied to the planning subproblem, while continuous time is applied to the scheduling of ethylene cracking and polymerization processes in the petrochemical site. An enterprise-wide mathematical model is formulated through mixed integer nonlinear programming. To solve the problem efficiently, a heuristic algorithm combined with a convolutional neural network (CNN), is proposed. Binary variables are used as the CNN input, leading to the integration of a data-driven approach and classical optimization by which a heuristic algorithm is established. The results do not only illustrate the detailed operations in a refinery and petrochemical complex under planning and scheduling, but also confirm the high efficiency of the proposed algorithm for solving large-scale problems.

关键词： planning scheduling refinery-petrochemical convolutional neural network heuristic algorithm

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An improved artificial bee colony algorithm with MaxTF heuristic rule for two-sided assembly line balancing

Xiaokun DUAN, Bo WU, Youmin HU, Jie LIU, Jing XIONG

《机械工程前沿（英文）》 2019年第14卷第2期页码 241-253 doi: 10.1007/s11465-018-0518-6

摘要： Two-sided assembly line is usually used for the assembly of large products such as cars, buses, and trucks. With the development of technical progress, the assembly line needs to be reconfigured and the cycle time of the line should be optimized to satisfy the new assembly process. Two-sided assembly line balancing with the objective of minimizing the cycle time is called TALBP-2. This paper proposes an improved artificial bee colony (IABC) algorithm with the MaxTF heuristic rule. In the heuristic initialization process, the MaxTF rule defines a new task’s priority weight. On the basis of priority weight, the assignment of tasks is reasonable and the quality of an initial solution is high. In the IABC algorithm, two neighborhood strategies are embedded to balance the exploitation and exploration abilities of the algorithm. The employed bees and onlooker bees produce neighboring solutions in different promising regions to accelerate the convergence rate. Furthermore, a well-designed random strategy of scout bees is developed to escape local optima. The experimental results demonstrate that the proposed MaxTF rule performs better than other heuristic rules, as it can find the best solution for all the 10 test cases. A comparison of the IABC algorithm and other algorithms proves the effectiveness of the proposed IABC algorithm. The results also denote that the IABC algorithm is efficient and stable in minimizing the cycle time for the TALBP-2, and it can find 20 new best solutions among 25 large-sized problem cases.

关键词： two-sided assembly line balancing problem artificial bee colony algorithm heuristic rules time boundary

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Determination of a suitable index for a solvent via two-column extractive distillation using a heuristic

Zhaoyou Zhu, Guoxuan Li, Yao Dai, Peizhe Cui, Dongmei Xu, Yinglong Wang

《化学科学与工程前沿（英文）》 2020年第14卷第5期页码 824-833 doi: 10.1007/s11705-019-1867-3

摘要： The traditional approach to solvent selection in the extractive distillation process strictly focuses on the change in the relative volatility of light-heavy components induced by the solvent. However, the total annual cost of the process may not be minimal when the solvent induces the largest change in relative volatility. This work presents a heuristic method for selecting the optimal solvent to minimize the total annual cost. The functional relationship between the relative volatility and the total annual cost is established, where the main factors, such as the relative volatility of the light-heavy components and the relative volatility of the heavy-component solvent, are taken into account. Binary azeotropic mixtures of methanol-toluene and methanol-acetone are separated to verify the feasibility of the model. The results show that using the solvent with the minimal two-column extractive distillation index, the process achieves a minimal total annual cost. The method is conducive for sustainable advancements in chemistry and engineering because a suitable solvent can be selected without simulation verification.

关键词： heuristic method solvent selection extractive distillation total annual cost

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An efficient two-stage approach for structural damage detection using meta-heuristic algorithms and group

Hamed FATHNEJAT, Behrouz AHMADI-NEDUSHAN

《结构与土木工程前沿（英文）》 2020年第14卷第4期页码 907-929 doi: 10.1007/s11709-020-0628-1

摘要： In this study, the performance of an efficient two-stage methodology which is applied in a damage detection system using a surrogate model of the structure has been investigated. In the first stage, in order to locate the damage accurately, the performance of the modal strain energy based index for using different numbers of natural mode shapes has been evaluated using the confusion matrix. In the second stage, to estimate the damage extent, the sensitivity of most used modal properties due to damage, such as natural frequency and flexibility matrix is compared with the mean normalized modal strain energy (MNMSE) of suspected damaged elements. Moreover, a modal property change vector is evaluated using the group method of data handling (GMDH) network as a surrogate model during damage extent estimation by optimization algorithm; in this part of methodology, the performance of the three popular optimization algorithms including particle swarm optimization (PSO), bat algorithm (BA), and colliding bodies optimization (CBO) is examined and in this regard, root mean square deviation ( ) based on the modal property change vector has been proposed as an objective function. Furthermore, the effect of noise in the measurement of structural responses by the sensors has also been studied. Finally, in order to achieve the most generalized neural network as a surrogate model, GMDH performance is compared with a properly trained cascade feed-forward neural network (CFNN) with log-sigmoid hidden layer transfer function. The results indicate that the accuracy of damage extent estimation is acceptable in the case of integration of PSO and MNMSE. Moreover, the GMDH model is also more efficient and mimics the behavior of the structure slightly better than CFNN model.

关键词： two-stage method modal strain energy surrogate model GMDH optimization damage detection

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Prediction of hydro-suction dredging depth using data-driven methods

《结构与土木工程前沿（英文）》 2021年第15卷第3期页码 652-664 doi: 10.1007/s11709-021-0719-7

摘要： In this study, data-driven methods (DDMs) including different kinds of group method of data handling (GMDH) hybrid models with particle swarm optimization (PSO) and Henry gas solubility optimization (HGSO) methods, and simple equations methods were applied to simulate the maximum hydro-suction dredging depth (h_s). Sixty-seven experiments were conducted under different hydraulic conditions to measure the h_s. Also, 33 data samples from three previous studies were used. The model input variables consisted of pipeline diameter (d), the distance between the pipe inlet and sediment level (Z), the velocity of flow passing through the pipeline (u₀), the water head (H), and the medium size of particles (D₅₀). Data-driven simulation results indicated that the HGSO algorithm accurately trains the GMDH methods better than the PSO algorithm, whereas the PSO algorithm trained simple simulation equations more precisely. Among all used DDMs, the integrative GMDH-HGSO algorithm provided the highest accuracy (RMSE = 7.086 mm). The results also showed that the integrative GMDHs enhance the accuracy of polynomial GMDHs by ~14.65% (based on the RMSE).

关键词： sedimentation water resources dam engineering machine learning heuristic

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Heuristic solution using decision tree model for enhanced XML schema matching of bridge structural calculation

Sang I. PARK, Sang-Ho LEE

《结构与土木工程前沿（英文）》 2020年第14卷第6期页码 1403-1417 doi: 10.1007/s11709-020-0666-8

摘要： Research on the quality of data in a structural calculation document (SCD) is lacking, although the SCD of a bridge is used as an essential reference during the entire lifecycle of the facility. XML Schema matching enables qualitative improvement of the stored data. This study aimed to enhance the applicability of XML Schema matching, which improves the speed and quality of information stored in bridge SCDs. First, the authors proposed a method of reducing the computing time for the schema matching of bridge SCDs. The computing speed of schema matching was increased by 13 to 1800 times by reducing the checking process of the correlations. Second, the authors developed a heuristic solution for selecting the optimal weight factors used in the matching process to maintain a high accuracy by introducing a decision tree. The decision tree model was built using the content elements stored in the SCD, design companies, bridge types, and weight factors as input variables, and the matching accuracy as the target variable. The inverse-calculation method was applied to extract the weight factors from the decision tree model for high-accuracy schema matching results.

关键词： structural calculation document bridge structure XML Schema matching weight factor data mining decision tree model

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Assessment of novel nature-inspired fuzzy models for predicting long contraction scouring and related uncertainties

《结构与土木工程前沿（英文）》 2021年第15卷第3期页码 665-681 doi: 10.1007/s11709-021-0713-0

摘要： The scouring phenomenon is one of the major problems experienced in hydraulic engineering. In this study, an adaptive neuro-fuzzy inference system is hybridized with several evolutionary approaches, including the ant colony optimization, genetic algorithm, teaching-learning-based optimization, biogeographical-based optimization, and invasive weed optimization for estimating the long contraction scour depth. The proposed hybrid models are built using non-dimensional information collected from previous studies. The proposed hybrid intelligent models are evaluated using several statistical performance metrics and graphical presentations. Besides, the uncertainty of models, variables, and data are inspected. Based on the achieved modeling results, adaptive neuro-fuzzy inference system–biogeographic based optimization (ANFIS-BBO) provides superior prediction accuracy compared to others, with a maximum correlation coefficient (R_test = 0.923) and minimum root mean square error value (RMSE_test = 0.0193). Thus, the proposed ANFIS-BBO is a capable cost-effective method for predicting long contraction scouring, thus, contributing to the base knowledge of hydraulic structure sustainability.

关键词： long contraction scour prediction uncertainty ANFIS model meta-heuristic algorithm

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求解复杂集装箱装载问题的新方法

王涛,魏凤

《中国工程科学》 2004年第6卷第12期页码 65-68

摘要：

提出了一种求解复杂集装箱装载问题的新方法，该方法将求解复杂装箱问题分成两步：首先，根据一定的启发式规则将集装箱进行体积最大化装载，并在深度方向根据货物将空间分层；然后，用遗传算法将各层进行重心位置最优化调整，使装载方案更加符合实际运输需要。实际应用结果表明，该方法在空间利用率、重心位置以及计算效率等方面都优于其他同类方法。

关键词：装载问题启发式重心遗传算法

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模拟系统的混合测试优化方法

梅文娟,刘震,李欧行,苏元章,梅渝松,龙泳吉

《信息与电子工程前沿（英文）》 2023年第24卷第9期页码 1302-1315 doi: 10.1631/FITEE.2200512

摘要：由于模拟系统在现代电子设备中起着至关重要作用，模拟系统测试优化已引起学术界和工业界广泛关注。尽管现有方法能实现测试策略的自动生成，但是由于复杂结构和多变的运行环境的影响，模拟系统难以有效生成诊断策略。因此，受到系统拓扑结构和冗余信息的影响，生成的测试策略在实际应用中缺乏可行性。此外，现有方法假设相互独立的测试项需要串行执行，增加了测试时间消耗。为解决上述问题，本文提出用于生成混合测试策略的启发式规划方法。实验证明，相较现有方法生成的策略，启发式规划方法和卷展启发式规划方法生成的策略具有更少层数和更低测试代价。通过对混合“或”节点的自适应优化和测试代价更新，该方法能提供更可行的优化方案并降低测试产生的代价。因此，本文提出的方法具有更高的优化效率。

关键词：故障诊断启发式搜索动态规划测试优化

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Optimal Method of Capacitated Lot-Sizing Planning in Manufacturing Systems

CHANG Jian-feng, ZHONG Yue-xian, HAN Zan-dong

《机械工程前沿（英文）》 2006年第1卷第1期页码 67-70 doi: 10.1007/s11465-005-0020-9

摘要：

This paper analyzes the capacitated lot-sizing problem considering an individual machine s production capacity using a two-layer hierarchical method to minimize the sum of the dynamic inventory cost and the overtime penalty cost. The genetic algorithm, the parameter linear programming method, and a heuristic method were used in the developed method. The method uses the genetic operator to define the lot-sizing matrix (the first layer), linear programming to determine eachmachine' s schedule (the second layer) according to the lot-sizing matrix, and the heuristic method to verify the feasibility of the solutions by adjusting them to meet the constraint requirements. The scheduling of machines in a press shop demonstrates the effectiveness of the algorithm. The result shows that the algorithm is convergent.

关键词： heuristic two-layer hierarchical algorithm constraint developed

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Application of the invasive weed optimization algorithm to economic dispatch problems

T. JAYABARATHI, Afshin YAZDANI, V. RAMESH

《能源前沿（英文）》 2012年第6卷第3期页码 255-259 doi: 10.1007/s11708-012-0202-1

摘要： In this paper the invasive weed optimization algorithm has been applied to a variety of economic dispatch (ED) problems. The ED problem is concerned with minimizing the fuel cost by optimally loading the electrical generators which are committed to supply a given demand. Some involve prohibited operating zones, transmission losses and valve point loading. In general, they are non-linear non-convex optimization problems which cannot be directly solved by conventional methods. In this work the invasive weed algorithm, a meta-heuristic method inspired by the proliferation of weeds, has been applied to four numerical examples and has resulted in promising solutions compared to published results.

关键词： economic dispatch (ED) invasive weed optimization non-convexity prohibited operating zones (POZ) valve point loading meta-heuristic

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Combined heat and power economic dispatch problem using firefly algorithm

Afshin YAZDANI, T. JAYABARATHI, V. RAMESH, T. RAGHUNATHAN

《能源前沿（英文）》 2013年第7卷第2期页码 133-139 doi: 10.1007/s11708-013-0248-8

摘要： Cogeneration units, which produce both heat and electric power, are found in many process industries. These industries also consume heat directly in addition to electricity. The cogeneration units operate only within a feasible zone. Each point within the feasible zone consists of a specific value of heat and electric power. These units are used along with other units, which produce either heat or power exclusively. Hence, the economic dispatch problem for these plants to optimize the fuel cost is quite complex and several classical and meta-heuristic algorithms have been proposed earlier. This paper applies the firefly algorithm, which is inspired by the behavior of fireflies which attract each other based on their luminosity. The results obtained have been compared with those obtained by other methods earlier and showed a marked improvement over the earlier methods.

关键词： combined heat and power (CHP) economic dispatch meta-heuristic algorithm firefly algorithm cogeneration

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KDD中双库协同机制的研究（Ⅱ）

杨炳儒,王建新,孙海洪

《中国工程科学》 2002年第4卷第5期页码 34-43

摘要：

在“KDD中双库协同机制的研究（Ⅰ）”的理论基础上，实现了对知识库的简约并实现了双库协同机制的两个协调器，从而建立了由KDD融入双库协同机制的新结构模型——KDD^*，这是一个在结构和功能上相对于KDD而言的开放的、优化的扩体。基于双库协同机制与KDD^*，提出了挖掘关联规则和聚类规则的新算法，充分体现了内在机理研究对主流发展的影响，开辟了一条全新的研究方向与路径。

关键词：知识发现双库协同机制启发型协调器中断型协调器 Maradbcm算法数值域划分算法

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Combined heat and power economic dispatch problem using the invasive weed optimization algorithm

T. JAYABARATHI, Afshin YAZDANI, V. RAMESH, T. RAGHUNATHAN

《能源前沿（英文）》 2014年第8卷第1期页码 25-30 doi: 10.1007/s11708-013-0276-4

摘要： Cogeneration units which produce both heat and electric power are found in many process industries. These industries also consume heat directly in addition to electricity. The cogeneration units operate only within a feasible zone. Each point within the feasible zone consists of a specific value of heat and electric power. These units are used along with other units which produce either heat or power exclusively. Hence the economic dispatch problem for these plants optimizing the fuel cost is quite complex and several classical and meta-heuristic algorithms have been proposed earlier. This paper applies the invasive weed optimization algorithm which is inspired by the ecological process of weed colonization and distribution. The results obtained have been compared with those obtained by other methods earlier and showed a marked improvement over earlier ones.

关键词： combined heat and power (CHP) economic dispatch meta-heuristic algorithm invasive weed optimization cogeneration