A LEVEL SET METHOD FOR STRUCTURAL TOPOLOGY OPTIMIZATION WITH MULTI-CONSTRAINTS AND MULTI-MATERIALS

Combining the vector level set model,the shape sensitivity analysis theory with the gradient projection technique,a level set method for topology optimization with multi-constraints and multi-materials is presented in this paper.The method implicitly describes structural material in- terfaces by the vector level set and achieves the optimal shape and topology through the continuous evolution of the material interfaces in the structure.In order to increase computational efficiency for a fast convergence,an appropriate nonlinear speed mapping is established in the tangential space of the active constraints.Meanwhile,in order to overcome the numerical instability of general topology opti- mization problems,the regularization with the mean curvature flow is utilized to maintain the interface smoothness during the optimization process.The numerical examples demonstrate that the approach possesses a good flexibility in handling topological changes and gives an interface representation in a high fidelity,compared with other methods based on explicit boundary variations in the literature.

Surface Deformation with Multi-constraints Based on the Minimum Energy

A method for deformation of 3D point clouds models was proposed with multi-constraints including arc-length constraints and multi-points position constraints. The energy function was built for the polyline which had been converted from the curve. Based on the minimum energy curve method, the curve on the mesh was deformed. The test results show that the proposed method has good performance. Compared with the other method,shape preserving of the curve is better. Finally,this method is used for the deformation of the 3D mannequin model. Circumference changes of the mannequin model can be reflected by the arc-length change in the size of the cross section.

A Multi-Constraint Path Optimization Scheme Based on Information Fusion in Software Defined Network

The existingmultipath routing in Software Defined Network (SDN) is relatively blind and inefficient, and there is alack of cooperation between the terminal and network sides, making it difficult to achieve dynamic adaptationof service requirements and network resources. To address these issues, we propose a multi-constraint pathoptimization scheme based on information fusion in SDN. The proposed scheme collects network topology andnetwork state information on the network side and computes disjoint paths between end hosts. It uses the FuzzyAnalytic Hierarchy Process (FAHP) to calculate the weight coefficients of multiple constrained parameters andconstructs a composite quality evaluation function for the paths to determine the priority of the disjoint paths. TheSDN controller extracts the service attributes by analyzing the packet header and selects the optimal path for flowrule forwarding. Furthermore, the service attributes are fed back to the path composite quality evaluation function,and the path priority is dynamically adjusted to achieve dynamic adaptation between service requirements andnetwork status. By continuously monitoring and analyzing the service attributes, the scheme can ensure optimalrouting decisions in response to varying network conditions and evolving service demands. The experimentalresults demonstrated that the proposed scheme can effectively improve average throughput and link utilizationwhile meeting the Quality of Service (QoS) requirements of various applications.

A multi-constraints based pose coordination model for large volume components assembly

In the assembly process of large volume product,engineering constraints limit the relative pose of components and serve as a standard for judging assembly quality.However,in the traditional process of target pose estimation,a general method is needed for establishing the correlation between engineering constraints and product pose,and it is difficult to evaluate pose by constraints comprehensively.Therefore,the process of target pose estimation and evaluation is separated.In this paper,a pose coordination model based on multi-constraints is proposed,which includes pre-processing,pose estimation,pose adjustment and evaluation.Firstly,engineering constraints are decoupled into 4 types of Minimum Geometrical Reference Constraints(MGRC),and the inequalities for solving target pose are formulated.Then the Constraint Coordination Index(CCI)is defined as the optimization objective to solve the target pose.Finally,with CCI as the numerical index,the target pose is evaluated to illustrate the quality of assembly.Taking the simulation experiment of wing-fuselage jointing as an example,the external and internal parameters of model are analyzed,and the pose estimation based on multi-constraints reduces the CCI by 12%,compared with the point-set-registration method.

The Information Modeling and Intelligent Optimization Method for Logistics Vehicle Routing and Scheduling with Multi-objective and Multi-constraint

The vehicle routing and scheduling (VRS) problem with multi-objective and multi-constraint is analyzed, considering the complexity of the modern logistics in city economy and daily life based on the system engineering. The objective and constraint includes loading, the dispatch and arrival time, transportation conditions,total cost,etc. An information model and a mathematical model are built,and a method based on knowledge and biologic immunity is put forward for optimizing and evaluating the programs dimensions in vehicle routing and scheduling with multi-objective and multi-constraints. The proposed model and method are illustrated in a case study concerning a transport network, and the result shows that more optimization solutions can be easily obtained and the method is efficient and feasible. Comparing with the standard GA and the standard GA without time constraint,the computational time of the algorithm is less in this paper. And the probability of gaining optimal solution is bigger and the result is better under the condition of multi-constraint.

Intelligent decision-making method of TBM operating parameters based on multiple constraints and objective optimization

The decision-making method of tunnel boring machine(TBM)operating parameters has a significant guiding significance for TBM safe and efficient construction,and it has been one of the TBM tunneling research hotspots.For this purpose,this paper introduces an intelligent decision-making method of TBM operating parameters based on multiple constraints and objective optimization.First,linear cutting tests and numerical simulations are used to investigate the physical rules between different cutting parameters(penetration,cutter spacing,etc.)and rock compressive strength.Second,a dual-driven mapping of rock parameters and TBM operating parameters based on data mining and physical rules of rock breaking is established with high accuracy by combining rock-breaking rules and deep neural networks(DNNs).The decision-making method is established by dual-driven mapping,using the effective rock-breaking capacity and the rated value of mechanical parameters as constraints and the total excavation cost as the optimization objective.The best operational parameters can be obtained by searching for the revolutions per minute and penetration that correspond to the extremum of the constrained objective function.The practicability and effectiveness of the developed decision-making model is verified in the SecondWater Source Channel of Hangzhou,China,resulting in the average penetration rate increasing by 11.3%and the total cost decreasing by 10%.

Bio-Inspired Binary Bees Algorithm for a Two-Level Distribution Optimisation Problem

Two uncoupleable distributions, assigning missions to robots and allocating robots to home stations, accompany the use ofmobile service robots in hospitals.In the given problem, two workload-related objectives and five groups of constraints areproposed.A bio-mimicked Binary Bees Algorithm (BBA) is introduced to solve this multiobjective multiconstraint combinatorialoptimisation problem, in which constraint handling technique (Multiobjective Transformation, MOT), multiobjectiveevaluation method (nondominance selection), global search strategy (stochastic search in the variable space), local searchstrategy (Hamming neighbourhood exploitation), and post-processing means (feasibility selection) are the main issues.TheBBA is then demonstrated with a case study, presenting the execution process of the algorithm, and also explaining the change ofelite number in evolutionary process.Its optimisation result provides a group of feasible nondominated two-level distributionschemes.

Highly-Efficient Aerodynamic Optimal Design of Rotor Airfoil Using Viscous Adjoint Method

In order to overcome the efficiency problem of the conventional gradient-based optimal design method,a highly-efficient viscous adjoint-based RANS equations method is applied to the aerodynamic optimal design of hovering rotor airfoil.The C-shaped body-fitted mesh is firstly automatically generated around the airfoil by solving the Poisson equations,and the Navier-Stokes(N-S)equations combined with Spalart-Allmaras(S-A)one-equation turbulence model are used as the governing equations to acquire the reliable flowfield variables.Then,according to multi-constrained characteristics of the optimization of high lift/drag ratio for hovering rotor airfoil,its corresponding adjoint equations,boundary conditions and gradient expressions are newly derived.On these bases,two representative rotor airfoils,NACA0012 airfoil and SC1095 airfoil,are selected as numerical examples to optimize their synthesized aerodynamic characteristics about lift/drag ratio in hover,and better aerodynamic performance of optimal airfoils are obtained compared with the baseline.Furthermore,the new designed rotor with the optimized rotor airfoil has better hover aerodynamic characteristics compared with the baseline rotor.In contrast to the baseline airfoils optimized by the finite difference method,it is demonstrated that the adjoint optimal algorithm itself is practical and highly-efficient for the aerodynamic optimization of hover rotor airfoil.

A Novel Sliding-mode Guidance Law Based on Lie-group Method

Although the channel-decoupling assumption is often used in design of three-dimensional guidance laws, it loses its rationality for aircrafts with strong kinematics coupling because body rotation arises. To overcome this trouble, a novel guiding method was proposed based on Lie-group. After a model of 3D guidance is formulated using vectors, the precision guidance with ending angular constraints can be transformed into a problem involving the relation between directional angles and rotational angular velocities of certain vectors. When the guidance model is imposed a SO(3)-based description, a novel 3D sliding mode guidance law with ending angular constraints can be developed via Lie-group control method and variable structure control theory. Finally, the feasibility and performance of the guidance law were shown by simulating the examples.

Output tracking of delayed logical control networks with multi-constraint

In this study,the output tracking of delayed logical control networks(DLCNs)with state and control constraints is further investigated.Compared with other delays,state-dependent delay updates its value depending on the current state values and a pseudo-logical function.Multiple constraints mean that state values are constrained in a nonempty set and the design of the controller is conditioned.Using the semi-tensor product of matrices,dynamical equations of DLCNs are converted into an algebraic description,and an equivalent augmented system is constructed.Based on the augmented system,the output tracking problem is transformed into a set stabilization problem.A deformation of the state transition matrix is computed,and a necessary and sufficient condition is derived for the output tracking of a DLCN with multi-constraint.This condition is easily verified by mathematical software.In addition,the admissible state-feedback controller is designed to enable the outputs of the DLCN to track the reference signal.Finally,theoretical results are illustrated by an example.

Three-dimensional Large Landing Angle Guidance Based on Two-dimensional Guidance Laws

Both the design process and form of the three-dimensional （3D） suboptimal guidance law （3DSGL） are very complex. Therefore, we propose the use of two-dimensional （2D） guidance laws to meet the guidance requirements of 3D space. By analyzing the relationship between the flight-path angle and its projections on OXY and OXZ planes, we obtain the ideal design requirements of the guidance laws. Based on the requirements, we design a 2D suboptimal guidance law used in the horizontal plane; combining the 2D vertical suboptimal guidance law, we create a whole ballistic simulation of six degree-of-freedom. The results are compared with those using other three guidance modes in the case of large windage of the initial azimuth angle. When the proportional navigation guidance （PNG） law is used in the horizontal planes, the landing angle will obviously decrease. With the proposed guidance mode, the large landing angle can be realized and meet the guidance precision requirements. Moreover, the required overload can decrease to meet the control requirement. The effects of the proposed guidance mode are close to that of 3DSGL despite its very simple form.

3D Path Planning of the Solar Powered UAV in the Urban-Mountainous Environment with Multi-Objective and Multi-Constraint Based on the Enhanced Sparrow Search Algorithm Incorporating the Levy Flight Strategy

In response to practical application challenges in utilizing solar-powered unmanned aerial vehicle(UAV)for remote sensing,this study presents a three-dimensional path planning method tailored for urban-mountainous environment.Taking into account constraints related to the solar-powered UAV,terrain,and mission objectives,a multi-objective trajectory optimization model is transferred into a single-objective optimization problem with weight factors and multiconstraint and is developed with a focus on three key indicators:minimizing trajectory length,maximizing energy flow efficiency,and minimizing regional risk levels.Additionally,an enhanced sparrow search algorithm incorporating the Levy flight strategy(SSA-Levy)is introduced to address trajectory planning challenges in such complex environments.Through simulation,the proposed algorithm is compared with particle swarm optimization(PSO)and the regular sparrow search algorithm(SSA)across 17 standard test functions and a simplified simulation of urban-mountainous environments.The results of the simulation demonstrate the superior effectiveness of the designed improved SSA based on the Levy flight strategy for solving the established single-objective trajectory optimization model.