Multi-Agent Collaborative Task Planning with Uncertain Task Requirements

In response to the uncertainty of information of the injured in post disaster situations,considering constraints such as random chance and the quantity of rescue resource,the split deliv-ery vehicle routing problem with stochastic demands(SDVRPSD)model and the multi-depot split delivery heterogeneous vehicle routing problem with stochastic demands(MDSDHVRPSD)model are established.A two-stage hybrid variable neighborhood tabu search algorithm is designed for unmanned vehicle task planning to minimize the path cost of rescue plans.Simulation experiments show that the solution obtained by the algorithm can effectively reduce the rescue vehicle path cost and the rescue task completion time,with high optimization quality and certain portability.

Distributed blackboard decision-making framework for collaborative planning based on nested genetic algorithm

A distributed blackboard decision-making framework for collaborative planning based on nested genetic algorithm （NGA） is proposed. By using blackboard-based communication paradigm and shared data structure, multiple decision-makers （DMs） can collaboratively solve the tasks-platforms allocation scheduling problems dynamically through the coordinator. This methodo- logy combined with NGA maximizes tasks execution accuracy, also minimizes the weighted total workload of the DM which is measured in terms of intra-DM and inter-DM coordination. The intra-DM employs an optimization-based scheduling algorithm to match the tasks-platforms assignment request with its own platforms. The inter-DM coordinates the exchange of collaborative request information and platforms among DMs using the blackboard architecture. The numerical result shows that the proposed black- board DM framework based on NGA can obtain a near-optimal solution for the tasks-platforms collaborative planning problem. The assignment of platforms-tasks and the patterns of coordination can achieve a nice trade-off between intra-DM and inter-DM coordination workload.

Receding-Horizon Trajectory Planning for Under-Actuated Autonomous Vehicles Based on Collaborative Neurodynamic Optimization

This paper addresses a major issue in planning the trajectories of under-actuated autonomous vehicles based on neurodynamic optimization.A receding-horizon vehicle trajectory planning task is formulated as a sequential global optimization problem with weighted quadratic navigation functions and obstacle avoidance constraints based on given vehicle goal configurations.The feasibility of the formulated optimization problem is guaranteed under derived conditions.The optimization problem is sequentially solved via collaborative neurodynamic optimization in a neurodynamics-driven trajectory planning method/procedure.Simulation results with under-actuated unmanned wheeled vehicles and autonomous surface vehicles are elaborated to substantiate the efficacy of the neurodynamics-driven trajectory planning method.

Trajectory Planning of High Precision Collaborative Robots

In order to satisfy the high efficiency and high precision of collaborative robots,this work presents a novel trajectory planning method.First,in Cartesian space,a novel velocity look-ahead control algorithm and a cubic polynomial are combined to construct the end-effector trajectory of robots.Then,the joint trajectories can be obtained through the inverse kinematics.In order to improve the smoothness and stability in joint space,the joint trajectories are further adjusted based on the velocity look-ahead control algorithm and quintic B-spline.Finally,the proposed trajectory planning method is tested on a 4-DOF serial collaborative robot.The experimental results indicate that the collaborative robot achieves the high efficiency and high precision,which validates the effectiveness of the proposed method.

Multi-Agent System for Real Time Planning Using Collaborative Agents

Autonomous agents are an important area of research in the sense that they are proactive, and include: goal-directed and communication capabilities. Furthermore each goals of the agent are constantly changing in a dynamic environment. Part of the challenge is to automate the process corresponding to each agent in order that they find their own objectives. Agents do not have to work individually, but can work with others and develop a coordinated group of actions. These agents are highly appreciated, when real time problems are involved, meaning that an agent must be able to react within a specific time interval, considering external events. Our work focuses on the design of a multi-agent architecture consisting of autonomous agents capable of acting through a goal-directed with: a) constraints, b) real-time, and c) with incomplete knowledge of the environment. This paper shows a model of collaborative agents architecture that share a common knowledge source, allowing knowledge of the environment;where we analyze it and its changes, choosing the most promising way for achieving the goals of the agent, in order to keep the whole system working, even if a fault occurs.

Study on Multi-enterprise Collaborative Resource Planning Based Process-oriented Decision Model

Aiming to share the information,knowledge and optimizing resource via collaborating with multiple external partners across their supply chains,the concept model and system framework of multi-enterprises collaborative resource planning (MECORP) are put forward.While there is Considerable pressure to improve the operation of MECORP system,their inherent complexity can make modelling a MECORP system a difficult task.Yet there could be considerable benefits in designing MECORP taking into account the operation of the system.In order to address the central research issue of developing of a methodology that can assist a manager in making decisions by modelling the operation of MECORP system.The methodology called process-oriented deci- sion model (PODM) is presented in the paper.This uses an abstracted network to model MECORP system.The MECORP system supported by PODM,can effective optimize the manifold resource,coordinate the relationship of multiple partners and assist deci- sion.Finally,an industry excample of MECORP system is described to illustrate the application of PODM.

Collaborative production planning between supply chain partners by Lagrangian relaxation

A collaborative planning framework based on the Lagrangian Relaxation was developed to coordinate and optimize the production planning of independent partners in multiple tier supply chains. Linking constraints and dependent demand constraints were added to the monolithic Multi-Level, multi-item Capacitated Lot Sizing Problem (MLCLSP). MLCLSP was Lagrangian relaxed and decomposed into facility-separable subproblems. Surrogate gradient algorithm was used to update Lagrangian multipliers, which coordinate decentralized decisions of the facilities. Production planning of independent partners could be appropriately coordinated and optimized by this framework without intruding their decisionities and private information. Experimental results show that the proposed coordination mechanism and procedure come close to optimal results as obtained by central coordination.

Conceptual Model for Collaborative Planning in Iran with Emphasis on the Role of Urban Planners： A Case Study of Anzali＇s Development Strategy

Nowadays, public participation is one of the most important factors to improve the feasibility, legitimacy and quality of urban plans. In Iran, due to lack of comprehensive understanding about the participation notion and its necessary socio-economic and political infrastructures, participatory decision-making has faced with some serious challenges in both processes of preparing and implementing. The present paper focuses on providing practical strategies for preparing collaborative urban plans in Iran＇s conditions. Also it seeks to answer this question： What is the role of planners to prepare a real collaborative plan？ It is assumed that a conceptual model for collaborative planning can be fitted with Iran＇s conditions by means of integrating the fundamental philosophic ideas of participatory planning such as theories of Paul Michel Foucault and Jürgen Habermas, given the fact that the present situation of collaborative planning in Iran needs a supportive theory which is compatible with power structures of Iranian urban planning system. In this regard, the Habermas＇ theory of “communicative action” and the Foucault＇s theory of “power structures” are reviewed by a comparative analysis methodology to present an integrated conceptual model for collaborative planning in Iran＇s condition. At the end, the CDS （City Development Strategy）---making process of Anzali City of Iran is analysed to examine this claim in the practice. The results yield that enabling urban planners to act as communication facilitators during planning can direct the collaborative planning in Iran from theory to a real practice by means of integrating the positive aspects of communication and power.

Multi-User Collaborative Assembly Planning over the Internet

Due to the increasing complexity of products and for the distributed product development, more closely collaborative work among designers is required. A collaborative assembly planning approach is proposed to support assembly planning in a networked environment. The working procedure is depicted and the key techniques including collaborative-planning-oriented assembly decomposition modeling, assembly assignment modeling, and sub-plans merging are addressed. By incorporating visual models at client side with assembly application models at server side, a web-based supporting environment for collaborative assembly planning has been developed using VRML and Java-EAI techniques. A case study is given to illustrate the feasibility and validity of the idea.

Strategies for the Application of BIM Technology in the Collaborative Planning and Design of Urban Roads and Pipelines

Urban road construction and the laying of underground pipelines are both important elements in the improvement of urban infrastructure,while the construction of the two may affect and restrict each other if they are not planned systematically.Therefore,a synergistic design of urban roads and pipelines is needed to ensure the synergy of urban road construction and underground pipeline laying.This paper mainly analyzes the necessity of building information modeling(BIM)technology application in the collaborative planning and design of urban roads and pipelines,and explores the application strategy of BIM technology.

Ground threat prediction-based path planning of unmanned autonomous helicopter using hybrid enhanced artificial bee colony algorithm

Unmanned autonomous helicopter(UAH)path planning problem is an important component of the UAH mission planning system.Aiming to reduce the influence of non-complete ground threat information on UAH path planning,a ground threat prediction-based path planning method is proposed based on artificial bee colony(ABC)algorithm by collaborative thinking strategy.Firstly,a dynamic threat distribution probability model is developed based on the characteristics of typical ground threats.The dynamic no-fly zone of the UAH is simulated and established by calculating the distribution probability of ground threats in real time.Then,a dynamic path planning method for UAH is designed in complex environment based on the real-time prediction of ground threats.By adding the collision warning mechanism to the path planning model,the flight path could be dynamically adjusted according to changing no-fly zones.Furthermore,a hybrid enhanced ABC algorithm is proposed based on collaborative thinking strategy.The proposed algorithm applies the leader-member thinking mechanism to guide the direction of population evolution,and reduces the negative impact of local optimal solutions caused by collaborative learning update strategy,which makes the optimization performance of ABC algorithm more controllable and efficient.Finally,simulation results verify the feasibility and effectiveness of the proposed ground threat prediction path planning method.

A Lesson Plan Incorporating Collaborative Strategic Reading

This essay is going to have an in-depth analysis of the Collaborative Strategic Reading, a four-step reading comprehension strategy popular in the Western classrooms. It will start with some brief introduction about this instructional approach in company with its theoretical rationale and research evidence for its effectiveness of improving learners' reading competence. Focused on the previewing skill, the first step of the reading instruction, a modified lesson plan is designed in the Chinese high school setting, followed by justification of the major elements of the plan, and some practical implications.

Neural Dynamics for Distributed Collaborative Control of Manipulators With Time Delays

Time-delay phenomena extensively exist in practical systems,e.g.,multi-agent systems,bringing negative impacts on their stabilities.This work analyzes a collaborative control problem of redundant manipulators with time delays and proposes a time-delayed and distributed neural dynamics scheme.Under assumptions that the network topology is fixed and connected and the existing maximal time delay is no more than a threshold value,it is proved that all manipulators in the distributed network are able to reach a desired motion.The proposed distributed scheme with time delays considered is converted into a time-variant optimization problem,and a neural dynamics solver is designed to solve it online.Then,the proposed neural dynamics solver is proved to be stable,convergent and robust.Additionally,the allowable threshold value of time delay that ensures the proposed scheme’s stability is calculated.Illustrative examples and comparisons are provided to intuitively prove the validity of the proposed neural dynamics scheme and solver.

Delphi-Based Planning Approach in the Maritime Transport Chain

The objective of this paper is to illustrate behavioural aspects and a collaborative Delphi-based planning approach in the maritime transport chain. Therefore, this paper analyses changes in behavioural routines and governance structures in the maritime transport chain using a case study that depicts mutual projections of expected container transhipment moderated by a neutral third for reducing the uncertainty in planning within the whole maritime transport chain. The actors＇ different views on container transport are collected and directly confronted to an expert panel showing bounded rationality and thus asymmetric information can be circumvented The planning approach shows how actors＇ different internal planning can be improved and evident to the market. The whole maritime transport chain expects the future development in container transport which can be given by using collaborative Delphi-based planning. As a result, an overall picture for planning issues can be constituted, improving both individual planning of the actors and expected market growth.

Mathematical Modeling and a Multiswarm Collaborative Optimization Algorithm for Fuzzy Integrated Process Planning and Scheduling Problem

Considering both process planning and shop scheduling in manufacturing can fully utilize their complementarities,resulting in improved rationality of process routes and high-quality and efficient production. Hence,the study of Integrated Process Planning and Scheduling (IPPS) has become a hot topic in the current production field. However,when performing this integrated optimization,the uncertainty of processing time is a realistic key point that cannot be neglected. Thus,this paper investigates a Fuzzy IPPS (FIPPS) problem to minimize the maximum fuzzy completion time. Compared with the conventional IPPS problem,FIPPS considers the fuzzy process time in the uncertain production environment,which is more practical and realistic. However,it is difficult to solve the FIPPS problem due to the complicated fuzzy calculating rules. To solve this problem,this paper formulates a novel fuzzy mathematical model based on the process network graph and proposes a MultiSwarm Collaborative Optimization Algorithm (MSCOA) with an integrated encoding method to improve the optimization. Different swarms evolve in various directions and collaborate in a certain number of iterations. Moreover,the critical path searching method is introduced according to the triangular fuzzy number,allowing for the calculation of rules to enhance the local searching ability of MSCOA. The numerical experiments extended from the well-known Kim benchmark are conducted to test the performance of the proposed MSCOA. Compared with other competitive algorithms,the results obtained by MSCOA show significant advantages,thus proving its effectiveness in solving the FIPPS problem.

Multi-UAV Collaborative Trajectory Planning for 3D Terrain Based on CS-GJO Algorithm

Existing solutions for collaborative trajectory planning using multiple UAVs suffer from issues such as low accuracy,instability,and slow convergence.To address the aforementioned issues,this paper introduces a new method for multiple unmanned aerial vehicle(UAV)3D terrain cooperative trajectory planning based on the cuck0o search golden jackal optimization(CS-GJO)algorithm.A model for single UAV trajectory planning and a model for multi-UAV collaborative trajectory planning have been developed,and the problem of solving the models is restructured into an optimization problem.Building upon the original golden jackal optimization,the use of tent chaotic mapping aids in the generation of the golden jackal's inital population,thereby promoting population diversity.Subsequently,the position update strategy of the cuckoo search algorithm is combined for purpose of update the position information of individual golden jackals,effectively preventing the algorithm from getting stuck in local minima.Finally,the corresponding nonlinear control parameter were developed.The new parameters expedite the decrease in the convergence factor during the pre-exploration stage,resulting in an improved overall search speed of the algorithm.Moreover,they attenuate the decrease in the convergence factor during the post-exploration stage,thereby enhancing the algorithm's global search.The experimental results demonstrate that the CS-GJO algorithm efficiently and accurately accomplishes multi-UAV cooperative trajectory planning in a 3D environment.Compared with other comparative algorithms,the CS-GJO algorithm also has better stability,higher optimization accuracy,and faster convergence speed.

Collaborative Planning of Distributed Wind Power Generation and Distribution Network with Large-scale Heat Pumps

With the advancement of clean heating projects and the integration of large-scale distributed heat pumps into rural distribution networks in northern China,power grid companies face tremendous pressure to invest in power grid upgrades,which bring opportunities for renewable power generation integration.The combination of heating by distributed renewable energy with the flexible operation of heat pumps is a feasible alternative for dealing with grid reinforcement challenges resulting from heating electrification.In this paper,a mathematical model of the collaborative planning of distributed wind power generation(DWPG)and distribution network with large-scale heat pumps is developed.In this model,the operational flexibility of the heat pump load is fully considered and the requirements of a comfortable indoor temperature are met.By applying this model,the goals of not only increasing the profit of DWPG but also reducing the cost of the power grid upgrade can be achieved.

A Lesson Plan of Writing an Argument for Applied Essay Writing in Vo cational Education

This paper sets forth a tentative model of lesson planning for the writing module at the vocational education level,with argumentative essay writing as an illustration.First,it presents a summary account of the context where the course structure and learner needs are addressed.It,then,provides an overview of the lesson plan in terms of classroom processes,strategies and purposes.Finally,the paper proceeds to the theoretical and empirical justification of the lesson plan through recourse to earlier research findings.The model is intended to be implicational for writing teachers to prepare each lesson as an indispensable pre-instructional process.

协同治理视角下国土空间规划实践与思考——以江苏为例

国土空间规划是完善现代化治理手段、提升空间治理能力、推动区域协同发展的重要工具。在总结跨地区、全流程、多主体的协同治理框架下,基于江苏省市县国土空间总体规划多层次同步编制的实践,探讨国土空间总体规划推动区域协同治理的有效路径。跨区域协同治理通过城市定位协同、生态环境治理协同、交通协同、市政基础设施协同、文化协同等手段,实现不同空间协同治理目标的落实;全流程协同治理通过建立常态化沟通磋商机制,实现省市县的纵向传导反馈和多部门、多条线的横向寻求共识,化解跨界地区矛盾;多主体协同治理侧重制度建构,保障行政力、市场力和社会力的多元参与。

智能采煤机器人关键技术

采煤机是综采工作面的核心装备,研发智能采煤机器人是实现综采工作面智能化的关键。综合分析当前采煤机机器人化研究进程中的传感检测、位姿控制、速度控制、截割轨迹规划与跟踪控制等技术的研究现状,提出研发智能采煤机器人必须破解的“智能感知、位姿控制、速度控制、截割轨迹规划与跟踪控制、位-姿-速协同控制”五大关键技术,并给出解决方案。针对智能感知问题,提出了构建智能感知系统思路,给出了智能采煤机器人智能感知系统的架构,实现对运行状态、位姿、环境等全面感知,为智能采煤机器人安全、可靠运行提供保障;针对位姿控制问题,提出了智能PID位姿控制思路,给出了改进遗传算法的PID位姿控制方法,实现了智能采煤机器人位姿精准控制;针对速度控制问题,提出了融合“力-电”异构数据的截割载荷测量思路,给出了基于神经网络算法的截割载荷测量方法,实现了截割载荷的精准测量;提出牵引与截割速度自适应控制思路,给出了人工智能算法牵引与截割速度决策方法和滑模自抗扰控制的牵引与截割速度控制方法,实现了智能采煤机器人速度精准自适应控制;针对截割轨迹规划与跟踪控制问题,提出了截割轨迹精准规划思路,给出了融合地质数据和历史截割数据的截割轨迹规划模型,实现了截割轨迹的精准规划;提出了截割轨迹精准跟踪控制思路,给出了智能插补算法的截割轨迹跟踪控制方法,实现了智能采煤机器人截割轨迹高精度规划与精准跟踪控制;针对“位-姿-速”协同控制问题,提出了“位-姿-速”协同控制参数智能优化思路,给出了基于多系统互约束的改进粒子群“位-姿-速”协同控制参数优化方法,实现了智能采煤机器人智能高效作业。深入研究五大关键技术破解思路,有利于加快推动研发高性能、高效率、高可靠的智能采煤机器人。