城市区域多物流无人机协同任务分配

针对城市区域多无人机协同物流任务分配问题, 综合考虑不同无人机性能、物流时效性、飞行可靠性等影响因素, 以经济成本、时间损失和安全风险最小为目标函数, 构建多无人机协同物流任务分配模型。因问题规模大、求解复杂度高, 设计改进的量子粒子群算法进行求解。首先，为增强粒子遍历性和多样性, 采用均匀化级联Logistic映射进行粒子初始化; 其次，为避免算法陷入局部最优解, 引入基于高斯分布的粒子变异方式; 最后，为提高算法运行效率, 运用自适应惯性权重方法对粒子赋值。仿真实验结果表明，所构建的模型能够实现任务分配多目标优化, 贴近城市区域无人机物流配送实际; 所提算法与传统量子粒子群算法和遗传算法相比, 任务分配代价分别下降了5.9%和6.3%;并进一步对参数权重设置进行分析, 当3个子目标函数权重系数分别为0.225、0.275和0.500, 种群规模为150时, 算法规划的结果最优。     

考虑中断的制造型供应链协调调度模型

供应链协调调度能有效提高企业应对供应链中断的能力。以两阶段制造供应链为研究对象，研究了中断情境下具有交付时间约束的多产品类型制造供应链协调调度问题。制造商接到包含多产品类型的工件加工订单，各工件需经供应商处理为原材料工件后，交付给制造商处理为完成品，各工件均有一个独立的交付期。如果供应商单方面调整工件加工顺序，会导致制造商冲突成本的增加，需双方协商处理。以最小化供应商总拖期交付成本和最小化制造商总冲突成本为目标，基于收益共享契约协调机制，构建了考虑中断的制造型供应链协调调度模型。设计了一个融合自适应邻域搜索算子的混合自适应遗传算法。通过算例仿真，验证了所提模型与算法的有效性。     

基于培养卓越应用型人才的线性代数问题驱动与案例任务教学模式改革

本文分析了现行线性代数的教学问题,提出了问题驱动与案例任务相结合的教学模式,并以两个案例来说明了此种教学模式的优越性,培养了学生的应用和创新能力,提高了学生的学习兴趣与课堂教学质量.     

2018年天文学热点回眸

 天文学是一门以观测为基础的学科，其发展主要依靠观测和数据的支持。基于SAO/NASA Astrophysics Data System天文物理学数据系统中高被引文章并结合热点新闻报道，回顾了2018年天文学热点的进展和发现，以观测和基础研究、仪器研制及工具开发两大方面论述了2018年天文学研究热点。     

Homology Priority Task Scheduling in μC/OS-Ⅱ Real-Time Kernel

μC/OS-Ⅱ is an open source real-time kernel adopting priority preemptive schedule strategy. Aiming at the problem of μC/OS-Ⅱ failing to support homology priority tasks scheduling, an approach for solution is proposed. The basic idea is adding round-robin scheduling strategy in its original scheduler in order to schedule homology priority tasks through time slice roundrobin. Implementation approach is given in detail. Firstly, the Task Control Block （TCB） is extended. And then, a new priority index table is created, in which each index pointer points to a set of homology priority tasks. Eventually, on the basis of reconstructing μC/OS-Ⅱ real-time kernel, task scheduling module is rewritten. Otherwise, schedulability of homology task supported by modified kernel had been analyzed, and deadline formula of created homology tasks is given. By theoretical analysis and experiment verification, the modified kernel can support homology priority tasks scheduling, meanwhile, it also remains preemptive property of original μC/OS-Ⅱ.     

用遗传算法解决一类模糊流水车间调度问题

对同时考虑模糊加工时间和模糊交货期的模糊流水车间调度问题进行了研究 ,模糊加工时间用三角模糊数来表示 ,模糊交货期用梯形模糊数来表示。应用遗传算法搜索最优排序 ,在适应度函数处理中引入模糊数处理方法 ,以平均满意度最大作为优化目标。最后给出了实验结果和结论     

临汾凹陷区主要活动断裂卫星影像分析

论述了活动断裂的一般影像特征，对临汾凹陷区主要活动断裂构造的卫星影像进行了分析，从而论证了应用卫星影像可以查明活动断裂的具体特征、力学性质及活动方式等，使人类进一步认识断裂构造的活动规律，将其所造成的自然灾害损失降至最低。     

FROM MANUFACTURING SCHEDULING TO SUPPLY CHAIN COORDINATION：THE CONTROL OF COMPLEXITY AND UNCERTAINTY

With time-based competition and rapid technology advancements, effective manufacturingscheduling and supply chain coordination are critical to quickly respond to changing marketconditions. These problems, however, are difficult in view of inherent complexity and variousuncertainties involved. Based on a series of results by the authors, decomposition and coordination byusing Lagrangian relaxation is identified in this paper as an effective way to control complexity anduncertainty.A manufacturing scheduling problem is first formulated within the job shop context withuncertain order arrivals, processing times, due dates, and part priorities as a separable optimizationproblem. A solution methodology that combines Lagrangian relaxation, stochastic dynamicprogramming, and heuristics is developed. Method improvements to effectively solve large problemsare also highlighted. To extend manufacturing scheduling within a factory to coordinate autonomicmembers across chains of suppliers, a decentralized supply chai     

SCHEDULING PROBLEMS - AN OVERVIEW

There seems to be a significant gap between the theoretical and the practical aspects of scheduling problems in the job shop environment. Theoretically, scheduling systems are designed on the basis of an optimum approach to the scheduling model. However in the practice, the optimum that is built into the scheduling applications seems to face some challenges when dealing with the dynamic character of a scheduling system, for instance machine breakdown or change of orders. Scheduling systems have become quite complex in the past few years. Competitive business environments and shorter product life cycles are the imminent challenges being faced by many companies these days. These challenges push companies to anticipate a demand driven supply chain in their business environment. A demand-driven supply chain incorporates the customer view into the supply chain processes. As a consequence of this, scheduling as a core process of the demand-driven supply chain must also reflect the customer view. In addition,     

一种求解资源受限工程调度问题的遗传算法

针对资源受限工程调度问题的特点，设计了一种改进的遗传算法，对算法的编码方式和解码规则，适值函数，遗传算法、初始种群的产生方法进行了详细的说明，利用被普遍应用的标准问题对该算法进行了大量的测试，分析了算法参数和问题参数对算法效果的影响，取得了令人满意的结果。