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A Genetic Algorithm for Single Machine Scheduling with Fuzzy Processing Time and Multiple Objectives
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作者 吴超超 顾幸生 《Journal of Donghua University(English Edition)》 EI CAS 2004年第3期185-189,共5页
In this paper, by considering the fuzzy nature of the data in real-life problems, single machine scheduling problems with fuzzy processing time and multiple objectives are formulated and an efficient genetic algorithm... In this paper, by considering the fuzzy nature of the data in real-life problems, single machine scheduling problems with fuzzy processing time and multiple objectives are formulated and an efficient genetic algorithm which is suitable for solving these problems is proposed. As illustrative numerical examples, twenty jobs processing on a machine is considered. The feasibility and effectiveness of the proposed method have been demonstrated in the simulation. 展开更多
关键词 SCHEDULING single machine genetic algorithms fuzzy processing time multiple objectives
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Multiple objectives application approach to waste minimization
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作者 张清宇 《Journal of Zhejiang University Science》 CSCD 2002年第4期405-411,共7页
Besides economics and controllability, waste minimization has now become an objective in designing chemical processes, and usually leads to high costs of investment and operation. An attempt was made to minimize waste... Besides economics and controllability, waste minimization has now become an objective in designing chemical processes, and usually leads to high costs of investment and operation. An attempt was made to minimize waste discharged from chemical reaction processes during the design and modification process while the operation conditions were also optimized to meet the requirements of technology and economics. Multiobjectives decision nonlinear programming (NLP) was employed to optimize the operation conditions of a chemical reaction process and reduce waste. A modeling language package-SPEEDUP was used to simulate the process. This paper presents a case study of the benzene production process. The flowsheet factors affecting the economics and waste generation were examined. Constraints were imposed to reduce the number of objectives and carry out optimal calculations easily. After comparisons of all possible solutions, best-compromise approach was applied to meet technological requirements and minimize waste. 展开更多
关键词 Waste minimization multiple objectives optimization Chemical reaction process.
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Multiple-Object Tracking Using Histogram Stamp Extraction in CCTV Environments
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作者 Ye-Yeon Kang Geon Park +1 位作者 Hyun Yoo Kyungyong Chung 《Computers, Materials & Continua》 SCIE EI 2023年第12期3619-3635,共17页
Object tracking,an important technology in the field of image processing and computer vision,is used to continuously track a specific object or person in an image.This technology may be effective in identifying the sa... Object tracking,an important technology in the field of image processing and computer vision,is used to continuously track a specific object or person in an image.This technology may be effective in identifying the same person within one image,but it has limitations in handling multiple images owing to the difficulty in identifying whether the object appearing in other images is the same.When tracking the same object using two or more images,there must be a way to determine that objects existing in different images are the same object.Therefore,this paper attempts to determine the same object present in different images using color information among the unique information of the object.Thus,this study proposes a multiple-object-tracking method using histogram stamp extraction in closed-circuit television applications.The proposed method determines the presence or absence of a target object in an image by comparing the similarity between the image containing the target object and other images.To this end,a unique color value of the target object is extracted based on its color distribution in the image using three methods:mean,mode,and interquartile range.The Top-N accuracy method is used to analyze the accuracy of each method,and the results show that the mean method had an accuracy of 93.5%(Top-2).Furthermore,the positive prediction value experimental results show that the accuracy of the mean method was 65.7%.As a result of the analysis,it is possible to detect and track the same object present in different images using the unique color of the object.Through the results,it is possible to track the same object that can minimize manpower without using personal information when detecting objects in different images.In the last response speed experiment,it was shown that when the mean was used,the color extraction of the object was possible in real time with 0.016954 s.Through this,it is possible to detect and track the same object in real time when using the proposed method. 展开更多
关键词 Data mining deep learning object detection object tracking real-time object detection multiple object image processing
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OPTIMALITY CONDITIONS AND DUALITY RESULTS FOR NONSMOOTH VECTOR OPTIMIZATION PROBLEMS WITH THE MULTIPLE INTERVAL-VALUED OBJECTIVE FUNCTION 被引量:4
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作者 Tadeusz ANTCZAK 《Acta Mathematica Scientia》 SCIE CSCD 2017年第4期1133-1150,共18页
In this paper, both Fritz John and Karush-Kuhn-Tucker necessary optimality conditions are established for a (weakly) LU-efficient solution in the considered nonsmooth multiobjective programming problem with the mult... In this paper, both Fritz John and Karush-Kuhn-Tucker necessary optimality conditions are established for a (weakly) LU-efficient solution in the considered nonsmooth multiobjective programming problem with the multiple interval-objective function. Further, the sufficient optimality conditions for a (weakly) LU-efficient solution and several duality results in Mond-Weir sense are proved under assumptions that the functions constituting the considered nondifferentiable multiobjective programming problem with the multiple interval- objective function are convex. 展开更多
关键词 nonsmooth multiobjective programming problem with the multiple interval- objective function Fritz John necessary optimality conditions Karush-Kuhn- Tucker necessary optimality conditions (weakly) LU-efficient solution Mond- Weir duality
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Effective method for tracking multiple objects in real-time visual surveillance systems 被引量:2
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作者 Wang Yaonan Wan Qin Yu Hongshan 《Journal of Systems Engineering and Electronics》 SCIE EI CSCD 2009年第6期1167-1178,共12页
An object model-based tracking method is useful for tracking multiple objects, but the main difficulties are modeling objects reliably and tracking objects via models in successive frames. An effective tracking method... An object model-based tracking method is useful for tracking multiple objects, but the main difficulties are modeling objects reliably and tracking objects via models in successive frames. An effective tracking method using the object models is proposed to track multiple objects in a real-time visual surveillance system. Firstly, for detecting objects, an adaptive kernel density estimation method is utilized, which uses an adaptive bandwidth and features combining colour and gradient. Secondly, some models of objects are built for describing motion, shape and colour features. Then, a matching matrix is formed to analyze tracking situations. If objects are tracked under occlusions, the optimal "visual" object is found to represent the occluded object, and the posterior probability of pixel is used to determine which pixel is utilized for updating object models. Extensive experiments show that this method improves the accuracy and validity of tracking objects even under occlusions and is used in real-time visual surveillance systems. 展开更多
关键词 visual surveillance multiple object tracking object model matching matrix.
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Optical encryption of multiple three-dimensional objects based on multiple interferences and single-pixel digital holography 被引量:2
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作者 Ying Wang Qi Liu +1 位作者 Jun Wang Qiong-Hua Wang 《Chinese Physics B》 SCIE EI CAS CSCD 2018年第3期253-259,共7页
We present an optical encryption method of multiple three-dimensional objects based on multiple interferences and single-pixel digital holography. By modifying the Mach-Zehnder interferometer, the interference of the ... We present an optical encryption method of multiple three-dimensional objects based on multiple interferences and single-pixel digital holography. By modifying the Mach-Zehnder interferometer, the interference of the multiple objects beams and the one reference beam is used to simultaneously encrypt multiple objects into a ciphertext. During decryption, each three-dimensional object can be decrypted independently without having to decrypt other objects. Since the single- pixel digital holography based on compressive sensing theory is introduced, the encrypted data of this method is effectively reduced. In addition, recording fewer encrypted data can greatly reduce the bandwidth of network transmission. Moreover, the compressive sensing essentially serves as a secret key that makes an intruder attack invalid, which means that the system is more secure than the conventional encryption method. Simulation results demonstrate the feasibility of the proposed method and show that the system has good security performance. 展开更多
关键词 multiple three-dimensional objects encryption single-pixel digital holography phase-shifting in- terference compressive sensing
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Construction of the Intelligent and Multiple Object Decision Support System for Making Train Diagram 被引量:1
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作者 彭其渊 席庆 阎海峰 《Journal of Modern Transportation》 1999年第2期125-132,共8页
Multiple objects decision is used widely in many complex fields. In this paper an idea is provided to construct a train diagram intelligent multiple objects decision support system (TDIMODSS). And the reference point ... Multiple objects decision is used widely in many complex fields. In this paper an idea is provided to construct a train diagram intelligent multiple objects decision support system (TDIMODSS). And the reference point method is used to solve the complicated and large scale problems of making and adjusting train schedule. This paper focuses on the principle and framework of the model base, knowledge base of train diagram. It is shown that the TDIMODSS can solve the problems and their uncertainty in making train diagram, and can combine the expert knowledge, experience and judgement of a decision maker into the system. In addition to that, a friendly working environment is also presented, which brings together the human judgement, the adaptability to environment and the computerised information. 展开更多
关键词 train diagram COMPUTER multiple objects intelligent decision support system
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Scene-adaptive hierarchical data association and depth-invariant part-based appearance model for indoor multiple objects tracking 被引量:1
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作者 Hong Liu Can Wang Yuan Gao 《CAAI Transactions on Intelligence Technology》 2016年第3期210-224,共15页
Indoor multi-tracking is more challenging compared with outdoor tasks due to frequent occlusion, view-truncation, severe scale change and pose variation, which may bring considerable unreliability and ambiguity to tar... Indoor multi-tracking is more challenging compared with outdoor tasks due to frequent occlusion, view-truncation, severe scale change and pose variation, which may bring considerable unreliability and ambiguity to target representation and data association. So discriminative and reliable target representation is vital for accurate data association in multi-tracking. Pervious works always combine bunch of features to increase the discriminative power, but this is prone to error accumulation and unnecessary computational cost, which may increase ambiguity on the contrary. Moreover, reliability of a same feature in different scenes may vary a lot, especially for currently widespread network cameras, which are settled in various and complex indoor scenes, previous fixed feature selection schemes cannot meet general requirements. To properly handle these problems, first, we propose a scene-adaptive hierarchical data association scheme, which adaptively selects features with higher reliability on target representation in the applied scene, and gradually combines features to the minimum requirement of discriminating ambiguous targets; second, a novel depth-invariant part-based appearance model using RGB-D data is proposed which makes the appearance model robust to scale change, partial occlusion and view-truncation. The introduce of RGB-D data increases the diversity of features, which provides more types of features for feature selection in data association and enhances the final multi-tracking performance. We validate our method from several aspects including scene-adaptive feature selection scheme, hierarchical data association scheme and RGB-D based appearance modeling scheme in various indoor scenes, which demonstrates its effectiveness and efficiency on improving multi-tracking performances in various indoor scenes. 展开更多
关键词 multiple objects tracking Scene-adaptive Data association Appearance model RGB-D data
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A Primal-Dual Infeasible-Interior-Point Algorithm for Multiple Objective Linear Programming Problems
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作者 HUANGHui FEIPu-sheng YUANYuan 《Wuhan University Journal of Natural Sciences》 CAS 2005年第2期351-354,共4页
A primal-dual infeasible interior point algorithm for multiple objective linear programming (MOLP) problems was presented. In contrast to the current MOLP algorithm. moving through the interior of polytope but not con... A primal-dual infeasible interior point algorithm for multiple objective linear programming (MOLP) problems was presented. In contrast to the current MOLP algorithm. moving through the interior of polytope but not confining the iterates within the feasible region in our proposed algorithm result in a solution approach that is quite different and less sensitive to problem size, so providing the potential to dramatically improve the practical computation effectiveness. 展开更多
关键词 Key words multiple objective linear programming primal dual infeasible INTERIOR point algorithm
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Multiple Objective Test Design for Accelerated Destructive Degradation Tests
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作者 黄硕 杨军 +1 位作者 彭锐 赵宇 《Journal of Donghua University(English Edition)》 EI CAS 2015年第6期954-956,共3页
Accelerated destructive degradation tests(ADDTs)are powerful to provide reliability information in the degradation processes with destructive measurements.In order to carry out an ADDT efficiently,both the estimation ... Accelerated destructive degradation tests(ADDTs)are powerful to provide reliability information in the degradation processes with destructive measurements.In order to carry out an ADDT efficiently,both the estimation precision of parameters and the test cost should be considered.On the basis of the given degradation model and failure criterion,a multiple-objective optimization model for the design of ADDTs is proposed.Under constrains of the maximum measurement time,the total sample size and the number of stress levels,a comprehensive target function is suggested to reflect both the precision of lifetime estimation and total cost,and the optimal test plan is obtained,which is composed by optimal choices for samples size,measurement frequency,and the number of measurements at each stress level.A real example is illustrated to demonstrate the implementation of the proposed approach. 展开更多
关键词 accelerated destructive degradation tests(ADDTs) highly reliable products multiple objectives test cost asymptotic variance
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Optimization of CNC Turning Machining Parameters Based on Bp-DWMOPSO Algorithm
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作者 Jiang Li Jiutao Zhao +3 位作者 Qinhui Liu Laizheng Zhu Jinyi Guo Weijiu Zhang 《Computers, Materials & Continua》 SCIE EI 2023年第10期223-244,共22页
Cutting parameters have a significant impact on the machining effect.In order to reduce the machining time and improve the machining quality,this paper proposes an optimization algorithm based on Bp neural networkImpr... Cutting parameters have a significant impact on the machining effect.In order to reduce the machining time and improve the machining quality,this paper proposes an optimization algorithm based on Bp neural networkImproved Multi-Objective Particle Swarm(Bp-DWMOPSO).Firstly,this paper analyzes the existing problems in the traditional multi-objective particle swarm algorithm.Secondly,the Bp neural network model and the dynamic weight multi-objective particle swarm algorithm model are established.Finally,the Bp-DWMOPSO algorithm is designed based on the established models.In order to verify the effectiveness of the algorithm,this paper obtains the required data through equal probability orthogonal experiments on a typical Computer Numerical Control(CNC)turning machining case and uses the Bp-DWMOPSO algorithm for optimization.The experimental results show that the Cutting speed is 69.4 mm/min,the Feed speed is 0.05 mm/r,and the Depth of cut is 0.5 mm.The results show that the Bp-DWMOPSO algorithm can find the cutting parameters with a higher material removal rate and lower spindle load while ensuring the machining quality.This method provides a new idea for the optimization of turning machining parameters. 展开更多
关键词 Machining parameters Bp neural network multiple Objective Particle Swarm Optimization Bp-DWMOPSO algorithm
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Ensemble Based Learning with Accurate Motion Contrast Detection
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作者 M.Indirani S.Shankar 《Intelligent Automation & Soft Computing》 SCIE 2023年第2期1657-1674,共18页
Recent developments in computer vision applications have enabled detection of significant visual objects in video streams.Studies quoted in literature have detected objects from video streams using Spatiotemporal Parti... Recent developments in computer vision applications have enabled detection of significant visual objects in video streams.Studies quoted in literature have detected objects from video streams using Spatiotemporal Particle Swarm Optimization(SPSOM)and Incremental Deep Convolution Neural Networks(IDCNN)for detecting multiple objects.However,the study considered opticalflows resulting in assessing motion contrasts.Existing methods have issue with accuracy and error rates in motion contrast detection.Hence,the overall object detection performance is reduced significantly.Thus,consideration of object motions in videos efficiently is a critical issue to be solved.To overcome the above mentioned problems,this research work proposes a method involving ensemble approaches to and detect objects efficiently from video streams.This work uses a system modeled on swarm optimization and ensemble learning called Spatiotemporal Glowworm Swarm Optimization Model(SGSOM)for detecting multiple significant objects.A steady quality in motion contrasts is maintained in this work by using Chebyshev distance matrix.The proposed system achieves global optimization in its multiple object detection by exploiting spatial/temporal cues and local constraints.Its experimental results show that the proposed system scores 4.8%in Mean Absolute Error(MAE)while achieving 86%in accuracy,81.5%in precision,85%in recall and 81.6%in F-measure and thus proving its utility in detecting multiple objects. 展开更多
关键词 multiple significant objects ensemble based learning modified pooling layer based convolutional neural network spatiotemporal glowworm swarm optimization model
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System reliability-based robust design of deep foundation pit considering multiple failure modes
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作者 Li Hong Xiangyu Wang +3 位作者 Wengang Zhang Yongqin Li Runhong Zhang Chunxia Chen 《Geoscience Frontiers》 SCIE CAS CSCD 2024年第2期169-182,共14页
Recently,reliability-based design is a universal method to quantify negative influence of uncertainty in geotechnical engineering.However,for deep foundation pit,evaluating the system safety of retaining structures an... Recently,reliability-based design is a universal method to quantify negative influence of uncertainty in geotechnical engineering.However,for deep foundation pit,evaluating the system safety of retaining structures and finding cost-effective design points are main challenges.To address this,this study proposes a novel system reliability-based robust design method for retaining system of deep foundation pit and illustrated this method via a simplified case history in Suzhou,China.The proposed method included two parts:system reliability model and robust design method.Back Propagation Neural Network(BPNN)is used to fit limit state functions and conduct efficient reliability analysis.The common source random variable(CSRV)model are used to evaluate correlation between failure modes and determine the system reliability.Furthermore,based on the system reliability model,a robust design method is developed.This method aims to find cost-effective design points.To solve this problem,the third generation non-dominated genetic algorithm(NSGA-III)is adopted.The efficiency and accuracy of whole computations are improved by involving BPNN models and NSGA-III algorithm.The proposed method has a good performance in locating the balanced design point between safety and construction cost.Moreover,the proposed method can provide design points with reasonable stiffness distribution. 展开更多
关键词 System reliability Machine learning method Non-dominated sorting genetic algorithm Robust design multiple objective optimization models
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Conditional Random Field Tracking Model Based on a Visual Long Short Term Memory Network 被引量:3
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作者 Pei-Xin Liu Zhao-Sheng Zhu +1 位作者 Xiao-Feng Ye Xiao-Feng Li 《Journal of Electronic Science and Technology》 CAS CSCD 2020年第4期308-319,共12页
In dense pedestrian tracking,frequent object occlusions and close distances between objects cause difficulty when accurately estimating object trajectories.In this study,a conditional random field tracking model is es... In dense pedestrian tracking,frequent object occlusions and close distances between objects cause difficulty when accurately estimating object trajectories.In this study,a conditional random field tracking model is established by using a visual long short term memory network in the three-dimensional(3D)space and the motion estimations jointly performed on object trajectory segments.Object visual field information is added to the long short term memory network to improve the accuracy of the motion related object pair selection and motion estimation.To address the uncertainty of the length and interval of trajectory segments,a multimode long short term memory network is proposed for the object motion estimation.The tracking performance is evaluated using the PETS2009 dataset.The experimental results show that the proposed method achieves better performance than the tracking methods based on the independent motion estimation. 展开更多
关键词 Conditional random field(CRF) long short term memory network(LSTM) motion estimation multiple object tracking(MOT)
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A Real-Time Multi-Vehicle Tracking Framework in Intelligent Vehicular Networks 被引量:2
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作者 Huiyuan Fu Jun Guan +2 位作者 Feng Jing Chuanming Wang Huadong Ma 《China Communications》 SCIE CSCD 2021年第6期89-99,共11页
In this paper,we provide a new approach for intelligent traffic transportation in the intelligent vehicular networks,which aims at collecting the vehicles’locations,trajectories and other key driving parameters for t... In this paper,we provide a new approach for intelligent traffic transportation in the intelligent vehicular networks,which aims at collecting the vehicles’locations,trajectories and other key driving parameters for the time-critical autonomous driving’s requirement.The key of our method is a multi-vehicle tracking framework in the traffic monitoring scenario..Our proposed framework is composed of three modules:multi-vehicle detection,multi-vehicle association and miss-detected vehicle tracking.For the first module,we integrate self-attention mechanism into detector of using key point estimation for better detection effect.For the second module,we apply the multi-dimensional information for robustness promotion,including vehicle re-identification(Re-ID)features,historical trajectory information,and spatial position information For the third module,we re-track the miss-detected vehicles with occlusions in the first detection module.Besides,we utilize the asymmetric convolution and depth-wise separable convolution to reduce the model’s parameters for speed-up.Extensive experimental results show the effectiveness of our proposed multi-vehicle tracking framework. 展开更多
关键词 multiple object tracking vehicle detection vehicle re-identification single object tracking machine learning
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A survey: which features are required for dynamic visual simultaneous localization and mapping? 被引量:2
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作者 Zewen Xu Zheng Rong Yihong Wu 《Visual Computing for Industry,Biomedicine,and Art》 EI 2021年第1期183-198,共16页
In recent years,simultaneous localization and mapping in dynamic environments(dynamic SLAM)has attracted significant attention from both academia and industry.Some pioneering work on this technique has expanded the po... In recent years,simultaneous localization and mapping in dynamic environments(dynamic SLAM)has attracted significant attention from both academia and industry.Some pioneering work on this technique has expanded the potential of robotic applications.Compared to standard SLAM under the static world assumption,dynamic SLAM divides features into static and dynamic categories and leverages each type of feature properly.Therefore,dynamic SLAM can provide more robust localization for intelligent robots that operate in complex dynamic environments.Additionally,to meet the demands of some high-level tasks,dynamic SLAM can be integrated with multiple object tracking.This article presents a survey on dynamic SLAM from the perspective of feature choices.A discussion of the advantages and disadvantages of different visual features is provided in this article. 展开更多
关键词 Dynamic simultaneous localization and mapping multiple objects tracking Data association Object simultaneous localization and mapping Feature choices
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DYNAMIC RELOCATION OF PLANT/WAREHOUSE FACILITIES: A FAST COMPACT GENETIC ALGORITHM APPROACH 被引量:1
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作者 LiShugang WuZhiming PangXiaohong 《Chinese Journal of Mechanical Engineering》 SCIE EI CAS CSCD 2004年第1期51-54,共4页
The problem of dynamic relocation and phase-out of combined manufacturingplant and warehousing facilities in the supply chain are concerned. A multiple time/multipleobjective model is proposed to maximize total profit... The problem of dynamic relocation and phase-out of combined manufacturingplant and warehousing facilities in the supply chain are concerned. A multiple time/multipleobjective model is proposed to maximize total profit during the time horizon, minimize total accesstime from the plant/warehouse facilities to its suppliers and customers and maximize aggregatedlocal incentives during the time horizon. The relocation problem keeps the feature of NP-hard andwith the traditional method the optimal result cannot be got easily. So a compact genetic algorithm(CGA) is introduced to solve the problem. In order to accelerate the convergence speed of the CGA,the least square approach is introduced and a fast compact genetic algorithm (fCGA) is proposed.Finally, simulation results with the fCGA are compared with the CGA and classical integerprogramming (IP). The results show that the fCGA proposed is of high efficiency for Paretooptimality problem. 展开更多
关键词 multiple objectives Compact genetic algorithm Supply chain Least squareapproach RELOCATION
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Fast interactive segmentation algorithm of image sequences based on relative fuzzy connectedness 被引量:1
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作者 Tian Chunna Gao Xinbo 《Journal of Systems Engineering and Electronics》 SCIE EI CSCD 2005年第4期750-755,共6页
A fast interactive segmentation algorithm of image-sequences based on relative fuzzy connectedness is presented. In comparison with the original algorithm, the proposed one, with the same accuracy, accelerates the seg... A fast interactive segmentation algorithm of image-sequences based on relative fuzzy connectedness is presented. In comparison with the original algorithm, the proposed one, with the same accuracy, accelerates the segmentation speed by three times for single image. Meanwhile, this fast segmentation algorithm is extended from single object to multiple objects and from single-image to image-sequences. Thus the segmentation of multiple objects from complex hackground and batch segmentation of image-sequences can be achieved. In addition, a post-processing scheme is incorporated in this algorithm, which extracts smooth edge with one-pixel-width for each segmented object. The experimental results illustrate that the proposed algorithm can obtain the object regions of interest from medical image or image-sequences as well as man-made images quickly and reliably with only a little interaction. 展开更多
关键词 fuzzy connectedness interactive image segmentation image-sequences segmentation multiple objects segmentation fast algorithm.
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Optimality and Duality on Fractional Multi-objective Programming Under Semilocal E-convexity 被引量:1
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作者 HU Qing-jie XIA O Yun-hai CHEN Nei-ping 《Chinese Quarterly Journal of Mathematics》 CSCD 2009年第2期200-210,共11页
In this paper, some necessary and sufficient optimality conditions are obtained for a fractional multiple objective programming involving semilocal E-convex and related functions. Also, some dual results are establish... In this paper, some necessary and sufficient optimality conditions are obtained for a fractional multiple objective programming involving semilocal E-convex and related functions. Also, some dual results are established under this kind of generalized convex functions. Our results generalize the ones obtained by Preda[J Math Anal Appl, 288(2003) 365-382]. 展开更多
关键词 semilocal E-convex functions fractional multiple objective programming optimality conditions DUALITY
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Multi-objective route planning approach for timely searching tasks of a supervised robot
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作者 刘鹏 熊光明 +2 位作者 李勇 姜岩 龚建伟 《Journal of Beijing Institute of Technology》 EI CAS 2014年第4期481-489,共9页
To performance efficient searching for an operator-supervised mobile robot, a multiple objectives route planning approach is proposed considering timeliness and path cost. An improved fitness function for route planni... To performance efficient searching for an operator-supervised mobile robot, a multiple objectives route planning approach is proposed considering timeliness and path cost. An improved fitness function for route planning is proposed based on the multi-objective genetic algorithm (MOGA) for multiple objectives traveling salesman problem (MOTSP). Then, the path between two route nodes is generated based on the heuristic path planning method A *. A simplified timeliness function for route nodes is proposed to represent the timeliness of each node. Based on the proposed timeliness function, experiments are conducted using the proposed two-stage planning method. The experimental results show that the proposed MOGA with improved fitness function can perform the searching function well when the timeliness of the searching task needs to be taken into consideration. 展开更多
关键词 multiple objective optimization multi-objective genetic algorithm supervised robots route planning TIMELINESS
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