Application of Stork Optimization Algorithm for Solving Sustainable Lot Size Optimization

The efficiency of businesses is often hindered by the challenges encountered in traditional Supply Chain Manage-ment(SCM),which is characterized by elevated risks due to inadequate accountability and transparency.To address these challenges and improve operations in green manufacturing,optimization algorithms play a crucial role in supporting decision-making processes.In this study,we propose a solution to the green lot size optimization issue by leveraging bio-inspired algorithms,notably the Stork Optimization Algorithm(SOA).The SOA draws inspiration from the hunting and winter migration strategies employed by storks in nature.The theoretical framework of SOA is elaborated and mathematically modeled through two distinct phases:exploration,based on migration simulation,and exploitation,based on hunting strategy simulation.To tackle the green lot size optimization issue,our methodology involved gathering real-world data,which was then transformed into a simplified function with multiple constraints aimed at optimizing total costs and minimizing CO_(2) emissions.This function served as input for the SOA model.Subsequently,the SOA model was applied to identify the optimal lot size that strikes a balance between cost-effectiveness and sustainability.Through extensive experimentation,we compared the performance of SOA with twelve established metaheuristic algorithms,consistently demonstrating that SOA outperformed the others.This study’s contribution lies in providing an effective solution to the sustainable lot-size optimization dilemma,thereby reducing environmental impact and enhancing supply chain efficiency.The simulation findings underscore that SOA consistently achieves superior outcomes compared to existing optimization methodologies,making it a promising approach for green manufacturing and sustainable supply chain management.

Research on Planning and Design of Multi-Story Prefabricated Electric Bicycle Charging Parking Lot in Urban and Rural Areas

In recent years,disorderly parking and difficult charging of electric bicycles have been challenges in urban management.The rapid growth of electric bicycles is in contradiction with the lack of dedicated parking spaces and charging service facilities in towns and villages.To solve the issue of parking and charging electric bicycles in limited urban and rural spaces,prefabricated building technology is applied to the design of a multi-story electric bicycle parking lot.The multi-story prefabricated electric bicycle parking lot is utilized in urban and rural planning and design to upgrade parking facilities in old urban areas,land-constrained commercial areas,as well as counties,towns,and rural areas with inadequate municipal facilities.Multi-story prefabricated electric bicycle parking lots are the application exploration of industrial buildings,and promote the high-quality development planning and construction of towns and counties and villages.Compared with the single-story metal charging station,the multi-story assembled electric bicycle parking lot has the characteristics of integrating parking and charging,being more durable and safer in structure,accommodating a large number of vehicles,and improving the space utilization rate.

图像去噪LOT模型的分裂Bregman方法

基于分裂Bregman方法具有较快的收敛速度以及在迭代过程中保持正则化参数为一个常数的优点,提出用分裂Bregman方法来解图像去噪LOT模型的第2步.实验表明,与原始的梯度下降法相比较,该算法具有较快的收敛速度,又能较好地复原图像.

采用传统方法检验LOT和LOT-R维度时的问题及其出路

笔者在中国文化背景下对生活定向测验(Life Orientation Test ;LOT)与其修订版(LOT-R)的维度进行验证.采用主成分分析结合平行分析保留主成分数目,同时采用验证性因素分析比较不同模型对生活定向测验及其修订版反应数据的拟合.大多数测验形式都呈现出两个维度,违背了测验编制者假定的单维性,与西方大多数研究者的结果一致,但是得到的两个维度是有实质意义的还是由于项目形式造成的则很难确定.在传统的因素分析框架下很难解决生活定向测验的维度争议,未来的研究应该从项目反应的理想点过程出发对该测验的维度进行探索和验证.

多台机器流水作业中存在调整时间的Lot-streaming问题

多台机器流水作业的 Lot-streaming问题（简称LS），以往的研究都不考虑调整时间，固定分批数，寻找最优分批大小；本文对机器引入调整时间，研究同时决定最优分批数及分批大小，并给出了相应最优算法．

MINI VIDAS原装试剂Master lot丢失的处理

目的:了解MINI VIDAS荧光免疫分析仪原装试剂测试条(strip)识别条码的规律。方法:涂改测试条上原条码,并手工输入与新的Master lot相对应的识别条码。结果:VIDAS仪器能够识别输入新条码的测试条。结论:MINI VIDAS原装试剂测试条识别条码是有规律可循的。

一种新的基于修正LOT模型的图像放大算法

由于图像采集设备以及成像手段的日益更新,在图像处理领域中图像放大技术已经得到越来越多的关注和重视。基于对偶策略,文中提出了一种基于修正LOT模型的Chambolle对偶图像放大算法。由于对偶变量可以等价为图像的法向量,提出在模型的第一步,直接计算对偶变量来代替光滑化法向量。第二步,采用Chambolle对偶算法重构放大图像。两步模型由于结合了ROF模型与LLT模型,该模型可以更好地保持图像边缘的信息,同时在一定程度上也避免了"锯齿效应"的产生,使图像边缘尽可能保持平滑。数值实验表明,通过与双线性插值、LOT模型图像放大方法进行比较,文中算法取得了理想的视觉效果与更高的信噪比。

MINI VIDAS原装试剂Master lot丢失的处理

目的了解MINI VIDAS荧光免疫分析仪原装试剂测试条(strip)识别条码的规律。方法涂改测试条上原条码,并手工输入与新的Master lot相对应的识别条码。结果VIDAS仪器能够识别输入新条码的测试条。结论MINI VIDAS原装试剂测试条识别条码是有规律可循的。

人体词“手”和“lot”的认知语义研究

通过对汉语的"手"和彝语的"lot"的语义比较,以认知语言学理论为依据,揭示了汉彝两种语言中具体的人体词的隐喻认知过程,发现两种语言的人体词在语义发展上具有较多的共性,由于语言使用环境的不同,语义也存在一定的差异。

宫颈鳞癌年轻患者LOT术后卵巢内分泌功能和并发症分析

目的分析宫颈鳞癌年轻患者接受LOT手术方法治疗后,对患者卵巢内分泌功能产生的影响以及并发症发生情况。方法以70例宫颈鳞癌年轻患者为研究对象,患者均接受LOT手术方法进行治疗,根据患者术后是否继续接受放疗治疗对患者进行分级研究。比较分析接受LOT术治疗以及是否进行放疗治疗对患者卵巢内分泌功能产生的影响,以及患者并发症的发生情况。结果术后不接受放疗治疗的患者,FSH、LH水平以及Kupperman评分明显低于接受放疗治疗的患者,E2水平明显高于接受放疗治疗的患者,不放疗患者的卵巢功能正常率70%高于放疗患者卵巢功能正常率35%,差异有统计学意义(P<0.05),70例LOT手术治疗患者术后,出现了2例盆腔积液患者,以及3例疼痛患者,患者术后并发症发生率为7.1%(5/70)。结论对于接受LOT术以及术后放疗治疗的宫颈鳞癌年轻患者而言,在接受了放疗治疗之后,会导致患者血清各指标出现较显著的变化。而未接受放疗治疗的患者,术后卵巢功能正常率相对较高。

NEWTON'S THEOREM WITH RESPECT TO A LOT OFCENTERS AND THEIR APPLICATIONS

In this paper we shall extend the paper [1] to a separate Taylor's Theorem with respect to a lot of centers, namely Newton's Theorem Of a lot of centers. From it we obtain the analogous results in the paper [2]. namely an interpolation formula of the difference of higher order. Finally we give their applications.

Modeling and Solving Lot-Splitting Scheduling Problem Based on Process

In flexible job-shop batch scheduling problem, the optimal lot-size of different process is not always the same because of different processing time and set-up time. Even for the same process of the same workpiece, the choice of machine also affects the optimal lot-size. In addition, different choices of lot-size between the constrained processes will impact the manufacture efficiency. Considering that each process has its own appropriate lot-size, we put forward the concept of scheduling with lot-splitting based on process and set up the scheduling model of lot-splitting to critical path process as the core. The model could update the set of batch process and machine selection strategy dynamically to determine processing route and arrange proper lot-size for different processes, to achieve the purpose of optimizing the makespan and reducing the processing batches effectively. The experiment results show that, comparing with lot-splitting scheduling scheme based on workpiece, this model optimizes the makespan and improves the utilization efficiency of the machine. It also greatly decreases the machined batches （42%） and reduces the complexity of shop scheduling production management.

CAPACITATED LOT SIZING AND SCHEDULING PROBLEMS USING HYBRID GA/TS APPROACHES

The capacitated lot sizing and scheduling problem that involves indetermining the production amounts and release dates for several items over a given planning horizonare given to meet dynamic order demand without incurring backloggings. The problem consideringovertime capacity is studied. The mathematical model is presented, and a genetic algorithm (GA)approach is developed to solve the problem. The initial solutions are generated after usingheuristic method. Capacity balancing procedure is employed to stipulate the feasibility of thesolutions. In addition, a technique based on Tabu search (TS) is inserted into the genetic algorithmdeal with the scheduled overtime and help the convergence of algorithm. Computational simulation isconducted to test the efficiency of the proposed hybrid approach, which turns out to improve boththe solution quality and execution speed.

Collaborative supply chain planning under dynamic lot sizing costs with capacity decision

Studies show that supply chain cooperation improves supply chain performance. However, it remains a challenge to develop and implement the realistic supply chain cooperation scheme. We investigate a two-echelon supply chain planning problem with capacity acquisition decision under asymmetric cost and demand information. A simple negotiation-based coordination mechanism is developed to synchronize production/order strategies of a supplier and a buyer. The coordination scheme shows how the supplier and the buyer modify their production and order policy in order to find a joint economic lot sizing plan, which saves the overall supply chain cost. The allocation of the cooperation benefit is determined by negotiation. Due to the complexity of the multiple periods, multiple level supply chain lot sizing with capacity decision, a heuristic algorithm is developed to find coordination solutions. Finally, the results of the numerical study indicate the performance of supply chain coordination scheme.

Discrete Artificial Bee Colony Algorithm for Lot-streaming Flowshop with Total Flowtime Minimization

Unlike a traditional flowshop problem where a job is assumed to be indivisible, in the lot-streaming flowshop problem, a job is allowed to overlap its operations between successive machines by splitting it into a number of smaller sub-lots and moving the completed portion of the sub-lots to downstream machine. In this way, the production is accelerated. This paper presents a discrete artificial bee colony （DABC） algorithm for a lot-streaming flowshop scheduling problem with total flowtime criterion. Unlike the basic ABC algorithm, the proposed DABC algorithm represents a solution as a discrete job permutation. An efficient initialization scheme based on the extended Nawaz-Enscore-Ham heuristic is utilized to produce an initial population with a certain level of quality and diversity. Employed and onlooker bees generate new solutions in their neighborhood, whereas scout bees generate new solutions by performing insert operator and swap operator to the best solution found so far. Moreover, a simple but effective local search is embedded in the algorithm to enhance local exploitation capability. A comparative experiment is carried out with the existing discrete particle swarm optimization, hybrid genetic algorithm, threshold accepting, simulated annealing and ant colony optimization algorithms based on a total of 160 randomly generated instances. The experimental results show that the proposed DABC algorithm is quite effective for the lot-streaming flowshop with total flowtime criterion in terms of searching quality, robustness and effectiveness. This research provides the references to the optimization research on lot-streaming flowshop.

流水生产中存在调整时间的Lot－Streaming问题

对二台机器流水生产中的ＬＳ问题，以往的研究多为固定分批数，寻找最优分批大小；本文对机器引入调整时间，研究同时决定最优分批数及最优分批大小，并给出了相应最优算法．

The Quality of Medicines in Community Pharmacies in Riyadh, Saudi Arabia: A Lot Quality Assurance Sampling (LQAS)-Based Survey

Objectives: To classify community pharmacies (CPs) in Riyadh, Saudi Arabia, in terms of the quality of medicines sold by them, using?the lot quality assurance sampling (LQAS) technique with a predefined threshold. Methods: Riyadh CPs were divided into 2 categories (“lots” for the purpose of LQAS), i.e., chain and independent CPs. Upper and lower rate thresholds for CPs that sell low-quality medicines were predefined as 20% and 5%, respectively. Consumer and provider risks were predefined as 0.05 and 0.10, respectively. The calculated number of randomly selected CPs required in each lot was 36;then, sale of low-quality medicines in >3 CPs implies a prevalence of >20% of such CPs according to LQAS. A randomly selected brand of amoxicillin (selected as a quality indicator of medicines because it is both widely counterfeited and heat-sensitive) was purchased from each pharmacy by a “mystery shopper”, checked for authenticity, and analyzed for drug content and content uniformity using a validated HPLC method. Results: Substandard amoxicillin was purchased in 9 pharmacies (4 chains and 5 independent). Both lots were thus rejected as unacceptable, which may indicate that consumers in Riyadh are at risk of purchasing substandard medicines at CPs. Conclusions: The quality of medicines sold in CPs in Riyadh did not meet our acceptability criterion, and appropriate intervention by decision makers is recommended. LQAS proved to be a practical, economical, and statistically valid sampling method for surveying the quality of medicines. It should enable decision makers to allocate resources for improvement more efficiently.

基于蜂窝的窄带物联网(NB-loT)技术性能及应用

随着现代科学技术的发展进步,智能城市、大数据时代的来临,无线通信将实现万物连接。很多企业预计在未来都将实现全球物联网连接数达到千亿级的时代,目前已经出现了大量的物与物的连接,但是这些连接大多通过蓝牙、WiFi等短距通信技术承载,并不是移动运营商网络。为了满足不同物联网的需求,根据物联网业务特征和移动通信网络特点,窄带业务应用场景开展了增强移动网络通信功能的技术研究以适应蓬勃发展的物联网业务需求。当前我们需要的正是一些低速率但是又高品质保障的物联网,这样不仅便利了生活,也促进了通信技术的发展。本文就目前在窄带物联网方面的技术性能做了一些研究并对其应用方面进行了研究。

A Note on an Economic Lot-sizing Problem with Perishable Inventory and Economies of Scale Costs:Approximation Solutions and Worst Case Analysis

This paper presents an economic lot-sizing problem with perishable inventory and general economies of scale cost functions. For the case with backlogging allowed, a mathematical model is formulated, and several properties of the optimal solutions are explored. With the help of these optimality properties, a polynomial time approximation algorithm is developed by a new method. The new method adopts a shift technique to obtain a feasible solution of subproblem and takes the optimal solution of the subproblem as an approximation solution of our problem. The worst case performance for the approximation algorithm is proven to be （4√2 ＋ 5）/7. Finally, an instance illustrates that the bound is tight.

Improved Fruit Fly Optimization Algorithm for Solving Lot-Streaming Flow-Shop Scheduling Problem

An improved fruit fly optimization algorithm( iFOA) is proposed for solving the lot-streaming flow-shop scheduling problem( LSFSP) with equal-size sub-lots. In the proposed iFOA,a solution is encoded as two vectors to determine the splitting of jobs and the sequence of the sub-lots simultaneously. Based on the encoding scheme,three kinds of neighborhoods are developed for generating new solutions. To well balance the exploitation and exploration,two main search procedures are designed within the evolutionary search framework of the iFOA,including the neighborhood-based search( smell-vision-based search) and the global cooperation-based search. Finally,numerical testing results are provided,and the comparisons demonstrate the effectiveness of the proposed iFOA for solving the LSFSP.