基于改进D?Lite遗传算法路径规划研究

针对遗传算法在移动机器人路径规划中易产生早熟现象和收敛速度慢的问题,提出了改进的D~* Lite遗传算法。该算法将D~* Lite算法和遗传算法相结合,通过引入碰撞系数和可视检测技术以提高路径安全性,寻找最短路径。在遗传算法设计中加入动态调整交叉与变异概率,以解决算法在路径规划中因陷入局部最优值而不能到达目标点的问题。最后,通过实验仿真可知:与蚁群算法和免疫遗传算法相比,改进的D~* Lite遗传算法执行效率高,可以快速规划出全局最优路径。     

Strategic planning optimization for natural gas to liquid transportation fuel (GTL) systems

A strategic planning optimization model is proposed for a network of natural gas to liquids (GTL) systems, and it is solved using a rolling horizon strategy. The model formulation determines the strategic and tactical decisions of the GTL supply chain over a long time horizon. The decisions to build new GTL refineries may be made over the span of 30 years and their operations cover the span of 60 years. Multiple capacities of GTL refineries (i.e., 1, 5, 10, 50, and 200 thousand barrels per day) that produce gasoline, diesel, and kerosene commensurate to the United States demand ratio may exist in the network. The parameter inputs include the locations, availabilities, and prices of natural gas in the United States discretized by county, the delivery locations of fuel products, and the transportation costs of every input and output of the refinery, defined for each time period. Formulated as a large-scale mixed-integer linear optimization (MILP) model, the problem is solved using a rolling horizon strategy for tractability. Case studies on the state of Pennsylvania are presented for different planning schemes and their impact on the economic performance of the GTL network is discussed.     

无线传感器网络中移动sink节点的路径规划

在无线传感器网络中,大量感知数据汇集到sink节点的采集方法会导致sink节点附近的节点能量耗尽,造成能量空洞。针对该问题,利用移动的sink节点进行数据收集是一种解决方法,其中移动sink的路径规划成为一个重要的问题。提出了一个移动sink路径规划算法,将无线传感器中随机分布的节点划分为不同的子区域,寻找sink节点移动的最佳转向点,最终得到最优的移动路径,以实现无线传感器网络生命周期最大化。仿真实验表明,与现有方案相比,该算法能显著延长网络的生命周期。     

Generation expansion planning in electricity markets: A novel framework based on dynamic stochastic MPEC

This paper presents a novel framework for generation expansion planning (GEP) of restructured power systems under uncertainty in a multi-period horizon, which includes generation investment from a price maker perspective. The investment problem is modeled as a bi-level optimization problem. The first level problem includes decisions related to investment in order to maximize total profit in the planning horizon. The second level problem consists of maximizing social welfare where the power market is cleared. Rival uncertainties on offering and investment are modeled using sets of scenarios. The bi-level optimization problem is then converted to a dynamic stochastic MPEC and represented as a mixed integer linear program (MILP) after linearization. The proposed framework is examined on a typical six-bus power network, MAZANDARAN regional electric company (MREC) transmission network as an area of IRAN interconnected power system and IEEE RTS 24-bus network. Simulation results confirm that the proposed framework can be a useful tool for analyzing the behavior of investments in electricity markets.     

Rethinking Enterprise Architecture for Sustainable Energy System Development

The development of a sustainable energy system throughout an enterprise is a complex task, which requires an agile holistic approach. Such an approach needs to include a variety of objectives including energy strategy formation and strategic decision-making, which are directly related to the analysis and management of the main areas of sustainable development:The economic, technological, environmental, and social. These multidimensional requirements of sustainability are often difficult to achieve within the enterprise, because these aspects are interrelated and influenced by various internal and external environment factors. This paper first reviews the main challenges for an energy system, and then demonstrates how a strategic agile enterprise architecture driven approach could effectively guide the sustainable energy system development. The study presented in this paper provides a holistic approach that contributes to the advancement and usage of literature dealing with issues of sustainable energy system development and agile enterprise architecture, which has not been discussed before to any great extent.     

Ageing workforce management in manufacturing systems: state of the art and future research agenda

The workforce ageing phenomenon is recently affecting most of the Organisation for Economic Co-operation and Development (OECD) member countries, due to a general ageing of their populations and a higher average retirement age of the workforce. In this paper, the topic of ageing workforce management is addressed from a production research standpoint, with the aim of understanding how older workers can be supported and involved in a manufacturing system. First, the current state of the art related to the ageing workforce in production systems is presented. This is structured according to four main topics: (1) analysis and evaluation of ageing workers’ functional capacities, (2) consideration of ageing workers’ capacities in industrial system modelling and management, (3) analysis and exploitation of ageing workers’ expertise, (4) acknowledgement, analysis, design and integration of supporting technologies. Next, the discussion on the impact of the ageing workforce on manufacturing systems’ performances leads to the comparison of some technological advances that are related to the Industry 4.0 paradigms. Finally, a future research agenda on this topic is proposed, based on the same topics classification proposed for the literature analysis. Five different research areas are derived, suggesting future directions for appropriate research concerning the employ of older workers in production environments.     

Hybrid make-to-stock and make-to-order systems: a taxonomic review

Production planning and control (PPC) systems that employ aspects from both make-to-order (MTO) and make-to-stock (MTS) production control are known as hybrid MTS/MTO systems. While both MTO and MTS separately have been studied extensively, their combined use has received less attention. However, the literature on this topic is growing and this paper shows that the review performed in this paper is an important addition to the field. We categorise relevant literature according to a novel taxonomy and show that hybrid MTS/MTO production control can be used in different contexts. In addition, an overview of the modelling techniques and methods used in these papers is provided. Based on the reviewed literature, relevant research questions and directions for future research are identified. Finally, it is shown that hybrid MTS/MTO production control is prevalent in practice by discussing research with industrial applications. The paper contains an overview of research on hybrid MTS/MTO production control to be used as reference for researchers active in the field, and provides managerial insights and directions for future research on this topic.     

移动边缘计算环境下的动态资源分配策略

在通讯设备爆炸式增长的时代,移动边缘计算作为5G通讯技术的核心技术之一,对其进行合理的资源分配显得尤为重要。移动边缘计算的思想是把云计算中心下沉到基站部署(边缘云),使云计算中心更加靠近用户,以快速解决计算资源分配问题。但是,相对于大型的云计算中心,边缘云的计算资源有限,传统的虚拟机分配方式不足以灵活应对边缘云的计算资源分配问题。为解决此问题,提出一种根据用户综合需求变化的动态计算资源和频谱分配算法(DRFAA),采用"分治"策略,并将资源模拟成"流体"资源进行分配,以寻求较大的吞吐量和较低的传输时延。实验仿真结果显示,动态计算资源和频谱分配算法可以有效地降低用户与边缘云之间的传输时延,也可以提高边缘云的吞吐量。     

A lightweight autonomous MAV for indoor search and rescue

Micro Aerial Vehicles (MAVs) have great potentials to be applied for indoor search and rescue missions. In this paper, we propose a modular lightweight design of an autonomous MAV with integrated hardware and software. The MAV is equipped with the 2D laser scanner, camera, mission computer and flight controller, running all the computation onboard in real time. The onboard perception system includes a laser‐based SLAM module and a custom‐designed visual detection module. A dual Kalman filter design provides robust state estimation by multiple sensor fusion. Specifically, the fusion module provides robust altitude measurement in the circumstance of surface changing. In addition, indoor‐outdoor transition is explicitly handled by the fusion module. In order to efficiently navigate through obstacles and adapt to multiple tasks, a task tree‐based mission planning method is seamlessly integrated with path planning and control modules. The MAV is capable of searching and rescuing victims from unknown indoor environments effectively. It was validated by our award‐winning performance at the 2017 International Micro Air Vehicle Competition (IMAV 2017), held in Toulouse, France. The performance video is available on https://youtu.be/8H19ppS_VXM .     

A mathematical model for open pit mine production scheduling with Grade Engineering® and stockpiling

This paper presents the development and implementation of an innovative mixed integer programming based mathematical model for an open pit mining operation with Grade Engineering framework. Grade Engineering comprises a range of coarse-separation based pre-processing techniques that separate the desirable (i.e. high-grade) and undesirable (i.e. low-grade or uneconomic) materials and ensure the delivery of only selected quantity of high quality (or high-grade) material to energy, water, and cost-intensive processing plant. The model maximizes the net present value under a range of operational and processing constraints. Given that the proposed model is computationally complex, the authors employ a data pre-processing procedure and then evaluate the performance of the model at several practical instances using computation time, optimality gap, and the net present value as valid measures. In addition, a comparison of the proposed and traditional (without Grade Engineering) models reflects that the proposed model outperforms the traditional formulation.