Robust optimisation of sustainable food grain transportation with uncertain supply and intentional disruptions

The proliferating need for sustainability intervention in food grain transportation planning is anchoring the attention of researchers in the interests of stakeholders and environment at large. Uncertainty associated with food grain supply further intensifies the problem steering the need for designing robust, cost-efficient and sustainable models. In line with this, this paper aims to develop a robust and sustainable intermodal transportation model to facilitate single type of food grain commodity shipments while considering procurement uncertainty, greenhouse gas emissions, and intentional hub disruption. The problem is designed as a mixed integer non-linear robust optimisation model on a hub and spoke network for evaluating near optimal shipment quantity, route selection and hub location decisions. The robust optimisation approach considers minimisation of total relative regret associated with total cost subject to several real-time constraints. A version of Particle Swarm Optimisation with Differential Evolution is proposed to tackle the resulting NP-hard problem. The model is tested with two other state-of the art meta-heuristics for small, medium, and large datasets subject to different procurement scenarios inspired from real time food grain operations in Indian context. Finally, the solution is evaluated with respect to total cost, model and solution robustness for all instances.     

Optimal carbon reduction level and ordering quantity under financial constraints

Carbon tax policy is widely adopted by many countries to curb carbon emissions. In the context of carbon tax policy, firms have more incentive to improve carbon reduction levels by reducing their carbon tax costs. However, firms need to bear carbon reduction costs that may cause shortage of capital. Thus, firms may face problems of financial constraints, which may demotivate firms to produce greener products. To address the decision‐making challenges of firms in the contexts of carbon tax policy and financial constraints, we consider a supply chain with a manufacturer who produces green products and a retailer who sells these products. Our study develops five models to investigate the two firms’ optimal wholesale price, carbon reduction level and ordering quantity, according to the manufacturer and retailer with or without financial constraints. Our goal in this study is to explore how carbon tax policy and banks’ interest rates affect the profits of the two firms, supply chain and consumer surplus. Certain managerial insights are obtained as follows. We demonstrate that carbon tax policy and banks’ interest rates demotivate the manufacturer to produce greener products and demotivate the retailer to order more products. If the interest rate to the manufacturer (retailer) is relatively low, then the manufacturer with financial constraint benefits (harms) the consumers compared with the retailer with financial constraint. Importantly, our analysis suggests that carbon tax policy harms the firms but benefits consumers, and the government in some conditions should reduce unit carbon tax.     

基于修正幂律模型流体的柳叶形扶正器旋流规律及应用

为提高注水泥过程中水泥浆顶替效率，国内外愈来愈多地使用旋流扶正器。但是，目前旋流扶正器结构参数主要靠经验设计，缺乏理论基础也没有相关行业标准。针对依据文丘里效应设计的柳叶形旋流扶正器，基于修正幂律流体模型，构建了旋流扶正器旋流长度计算模型。通过数值模拟对旋流扶正器井下旋流规律进行研究，推导出了旋流扶正器在修正幂律流体条件下，周向平均速度和完全顶替的临界速度公式。基于旋流扶正器井下旋流规律，分析了井眼环空结构、流体性能、井下井壁附着力对水泥浆顶替效率的影响，优化了柳叶形旋流扶正器旋流角、扶正棱长度、扶正棱有效体积和扶正器高度等设计参数。对比分析了柳叶形与常规旋流扶正器在不同工况下的旋流长度，柳叶形扶正器的旋流长度比常规扇形平均提升了32%，比常规梯形扶正器平均提升了47%。柳叶形扶正器在新疆顺北油田顺北3井等20多井次超深井应用，应用井固井质量明显优于常规扇形的旋流扶正器。     

An intelligent EGWO-SCA-CS algorithm for PSS parameter tuning under system uncertainties

This paper proposes a novel hybrid technique called enhanced grey wolf optimization-sine cosine algorithm-cuckoo search (EGWO-SCA-CS) algorithm to improve the electrical power system stability. The proposed method comprises of a popular grey wolf optimization (GWO) in an enhanced and hybrid form. It embraces the well-balanced exploration and exploitation using the cuckoo search (CS) algorithm and enhanced search capability through the sine cosine algorithm (SCA) to elude the stuck to the local optima. The proposed technique is validated with the 23 benchmark functions and compared with state-of-the-art methods. The benchmark functions consist of unimodal, multimodal function from which the best suitability of the proposed technique can be identified. The robustness analysis also presented with the proposed method through boxplot, and a detailed statistical analysis is performed for a set of 30 individual runs. From the inferences gathered from the benchmark functions, the proposed technique is applied to the stability problem of a power system, which is heavily stressed with the nonlinear variation of the load and thereby operating conditions. The dynamics of power system components have been considered for the mathematical model of a multimachine system, and multiobjective function has been framed in tuning the optimal controller parameters. The effectiveness of the proposed algorithm has been assessed by considering two case studies, namely, (i) the optimal controller parameter tuning, and (ii) the coordination of oscillation damping devices in the power system stability enhancement. In the first case study, the power system stabilizer (PSS) is considered as a controller, and a self-clearing three-phase fault is considered as the system uncertainty. In contrast, static synchronous compensator (STATCOM) and PSS are considered as controllers to be coordinated, and perturbation in the system states as uncertainty in the second case study.     

Responsive supply in fashion mass customisation systems with consumer returns

Mass customisation systems have been well-established in the fashion industry. Some fashion brands offer the mass customisation system for their selected seasonal products, and allow unconditional returns and full refund for any unsatisfied customers. Motivated by the above mentioned observed industrial practice and based on the growing importance of responsive supply, we explore in this paper the value of quick response supply in fashion mass customisation systems with consumer returns. We focus on investigating how the consumer returns rate affects (i) the optimal inventory decision of the fashion brand, (ii) the achievability of Pareto improvement in implementing quick response supply, (iii) the respective values of quick response for the fashion brand, the fashion supplier and also the fashion supply chain, and (iv) the impact of quick response supply on the environment. We interestingly find that consumer returns enhance the value of quick response supply to the fashion supplier. Quick response supply is also found to be helpful in reducing the environmental cost under the fashion mass customisation system with consumer returns.     

非调制双色红外测温误差实时补偿方法研究

针对环境温度变化对双色红外测温准确度的影响,基于双色比色红外测温原理,分析了非调制双色红外测温的误差来源,提出一种新的快门式非调制双色红外测温方法。在光路中增加快门及其控制模块,控制快门闭合,将测得系统偏移作为补偿项,补偿实际测温时因温度变化给测量带来的误差。仿真结果表明,在600～1 100℃的测温范围内,长时间使用的无快门非调制红外双色测温的精度严重劣化,而快门式非调制双色红外测温的准确度大幅提高,可达到±0.5%。     

Design of Feedback Shift Register of Against Power Analysis Attack

Stream ciphers based on linear feedback shift register (LFSR) are suitable for constrained environments, such as satellite communications, radio frequency identification devices tag, sensor networks and Internet of Things, due to its simple hardware structures, high speed encryption and lower power consumption. LFSR, as a cryptographic primitive, has been used to generate a maximum period sequence. Because the switching of the status bits is regular, the power consumption of the LFSR is correlated in a linear way. As a result, the power consumption characteristics of stream cipher based on LFSR are vulnerable to leaking initialization vectors under the power attacks. In this paper, a new design of LFSR against power attacks is proposed. The power consumption characteristics of LFSR can be masked by using an additional LFSR and confused by adding a new filter Boolean function and a flip-flop. The design method has been implemented easily by circuits in this new design in comparison with the others.     

建筑材料供应中断对承包商成本的冲击研究——基于鲁棒模型分析

为了揭示供应商与承包商为主体的二级供应链中，两者间耦合作用条件下发生的供应中断对供应商最优决策及对承包商成本的影响机制，且剖析供应中断对承包商成本的冲击效应，以供应商存在高退出风险为研究对象，在仅知产量均值与方差条件下，运用Scarf提出的“极大极小值”鲁棒决策方法，通过设定不同决策情况下的供应链系统反馈，分析了不同退出标准情况下二级供应链的博弈过程。基于理论支撑下的鲁棒模型数值仿真结果得出：在退出标准α为100时，中间变量在290~350范围内，供应商存在最优决策，但承包商最优决策无法确定；与α为0时相比，在订货量达到一定状态，即α为140时，承包商成本增加了1.5%，表明承包商成本与供应商退出标准呈正相关，退出标准越高，对承包商成本造成的冲击效应越大。此研究结论为供应链初期不稳定且信息不完整条件下发生的供应中断影响机理提供了新的视角。     

高供氧压力下高马赫数氧枪数值模拟

  以北方某钢厂100 t转炉为原型，建立顶吹转炉炉内流场的三维数学模型，采用Fluent软件研究了不同高马赫数氧气射流与熔池钢液速度流场分布之间的依赖关系。研究发现，高马赫数氧枪在Ma（马赫数）为2.0～2.3时，曲线平稳，为最佳供氧压力。在提高供氧压力的同时，氧气射流的最大速度、熔池钢液面的冲击直径及冲击深度也随之增加。模拟结果显示，氧气射流在设计工况氧压小于1.0 MPa时，射流之间相互干扰作用最弱；氧气射流在设计工况氧压力大于1.0 MPa后，冲击直径与冲击深度增幅较小。基于上述研究，在实际生产中应用了高马赫数氧枪后，并结合变枪变压操作工艺，可以改善熔池底部钢液流动状况、稳定转炉吹炼过程、控制炉渣喷溅。     

选区激光熔化工艺参数对气雾化316L不锈钢粉末成形制品性能的影响

本研究系统考察了激光功率和扫描速度对316L不锈钢粉末选区激光熔化工艺成形熔道、制品微观组织及力学性能的影响,并分析了各类缺陷的形成原因。研究结果表明:在低激光功率和高扫描速度条件下,熔道中出现了大量球状颗粒,这些颗粒之间的空隙恶化了下一层粉末的熔化条件,这正是成形制品中熔道分布混乱以及孔洞、裂纹产生的根本原因,进而导致成形制品力学性能降低;在高激光功率和低扫描速度条件下,熔池快速升温/冷却的热应力作用增强,使得成形制品的熔道交界处也存在孔洞和裂纹等缺陷。在本研究实验条件下,激光功率为350 W,扫描速度为1750 mm/s时,SLM成形制品的力学性能最为优异,其中抗拉强度为731 MPa、屈服强度为638 MPa、断后伸长率为40.0%,致密度为96.27%。