柔性Job Shops集成调度启发式算法

为有效解决柔性作业车间(Job Shops)的加工与搬运集成调度问题,以最小化最大完工时间(Makespan)为调度目标,建立非线性规划模型,提出基于贪婪启发式策略的变邻域搜索算法(GRS-RVNS).根据准时(JIT)生产和均衡生产思想构建贪婪启发式策略快速求初始解.利用析取图表示可行解并根据析取图调度的性质定理构建有效的搜索邻域,进而利用随机变邻域搜索算法对初始解进行优化.对提出的算法进行仿真实验分析,结果表明:该算法求解时间短、调度方法有竞争性.

Hybrid evolutionary algorithm for no-wait flow shops to minimize makespan and total flowtime

The NP-hard no-wait flow shop scheduling problems with makespan and total flowtime minimization are considered. Objective increment properties of the problems are analyzed. A non-dominated classification method is introduced to class population individuals into Pareto fronts to improve searching efficiency. Besides investigating the crowding distance and the elitist solution strategy, two effective bi-criteria local search procedures based on objective increments are presented to improve searching effectiveness. Based on the properties and methods, a hybrid evolutionary algorithm is proposed for the considered problems and compared with the best existing algorithms. Experimental results show that the proposed algorithm is effective with high efficiency.

Protective Measures for Space Environment of Time-honored Brands——With Xi'an City as a Study Case

Based on the field survey and analysis of representative traditional time-honored shops in Xi'an City,specific measures for protecting their space environment were put forward,and the sustainable preservation and development pattern of such intangible cultural heritages in the future urban development was established.

一类随机型Flow Shops模型及其算法

提出一类特殊随机型 Flow Shops模型 ,给出若干基本结论 ,并在某种“对称性”

TikTok Shop在东南亚五国的发展策略研究——基于SWOT-AHP模型的分析

伴随全球电商渗透率持续提升,我国的一批优秀企业纷纷开通跨境电商平台,以更好地助力品牌出海。字节跳动旗下的全球最大的短视频网站之一Tiktok就是其中的典型代表,其在东南亚五国开通了Titok Shop,为我国企业开拓东南亚市场搭建优质的跨境电商平台。首先总结了TikTok Shop在东南亚五国开展业务的现状,采用SWO T-AHP方法对TikTok Shop在东南亚五国的发展进行深入剖析,认为其战略发展方向应以SO战略为主;提出TikTok Shop应完善跨境电商物流体系、深耕本土化运营、完善品牌化建设、加强基础设施建设、培养跨境电商复合型人才等发展策略,以期为我国企业搭建优质的跨境电商平台,助力我国品牌出海提供有价值的参考。

Food safety knowledge and practices of abattoir and butchery shops and the microbial profile of meat in Mekelle City,Ethiopia

Objective:To assess the food safety knowledge and practices in meat handling,and to determine microbial load and pathogenic organisms in meat at Mekelle city.Methods:A descriptive survey design was used to answer questions concerning the current status of food hygiene and sanitation practiced in the abattoir and butcher shops.Workers from the abattoir and butcher shops were interviewed through a structured questionnaire to assess their food safety knowledge.Bacterial load was assessed by serial dilution method and the major bacterial pathogens were isolated by using standard procedures.Results:15.1%of the abattoir workers had no health certificate and there was no hot water,sterilizer and cooling facility in the abattoir.11.3%of the butchers didn’t use protective clothes.There was a food safety knowledge gap within the abattoir and butcher shop workers.The mean values of bacterial load of abattoir meat,butcher shops and street meat sale was found to be 1.1×10~5,5.6×10~5and 4.3×10~6 cfu/g,respectively.The major bacterial pathogens isolated were Escherichia coli,Staphylococcus aureus and Bacillus cereus.Conclusions:The study revealed that there is a reasonable gap on food safely knowledge by abattoir and butcher shop workers.The microbial profile was also higher compared to standards set by World Health Organization.Due attention should be given by the government to improve the food safety knowledge and the quality standard of meat sold in the city.

A Cross Entropy-Genetic Algorithm for m-Machines No-Wait Job-ShopScheduling Problem

No-wait job-shop scheduling (NWJSS) problem is one of the classical scheduling problems that exist on many kinds of industry with no-wait constraint, such as metal working, plastic, chemical, and food industries. Several methods have been proposed to solve this problem, both exact (i.e. integer programming) and metaheuristic methods. Cross entropy (CE), as a new metaheuristic, can be an alternative method to solve NWJSS problem. This method has been used in combinatorial optimization, as well as multi-external optimization and rare-event simulation. On these problems, CE implementation results an optimal value with less computational time in average. However, using original CE to solve large scale NWJSS requires high computational time. Considering this shortcoming, this paper proposed a hybrid of cross entropy with genetic algorithm (GA), called CEGA, on m-machines NWJSS. The results are compared with other metaheuritics: Genetic Algorithm-Simulated Annealing (GASA) and hybrid tabu search. The results showed that CEGA providing better or at least equal makespans in comparison with the other two methods.

Dynamic Scheduling of Flexible Job Shops

Aim of this research is to minimize makespan in the flexible job shop environment by the use of genetic algorithms and scheduling rules. Software is developed using genetic algorithms and scheduling rules based on certain constraints such as non-preemption of jobs, recirculation, set up times, non-breakdown of machines etc. Purpose of the software is to develop a schedule for flexible job shop environment, which is a special case of job shop scheduling problem. Scheduling algorithm used in the software is verified and tested by using MT10 as benchmark problem, presented in the flexible job shop environment at the end. LEKIN software results are also compared with results of the developed software by the use of MT10 benchmark problem to show that the latter is a practical software and can be used successfully at BIT Training Workshop.

APPLYING PARTICLE SWARM OPTIMIZATION TO JOB-SHOPSCHEDULING PROBLEM

A new heuristic algorithm is proposed for the problem of finding the minimummakespan in the job-shop scheduling problem. The new algorithm is based on the principles ofparticle swarm optimization (PSO). PSO employs a collaborative population-based search, which isinspired by the social behavior of bird flocking. It combines local search (by self experience) andglobal search (by neighboring experience), possessing high search efficiency. Simulated annealing(SA) employs certain probability to avoid becoming trapped in a local optimum and the search processcan be controlled by the cooling schedule. By reasonably combining these two different searchalgorithms, a general, fast and easily implemented hybrid optimization algorithm, named HPSO, isdeveloped. The effectiveness and efficiency of the proposed PSO-based algorithm are demonstrated byapplying it to some benchmark job-shop scheduling problems and comparing results with otheralgorithms in literature. Comparing results indicate that PSO-based algorithm is a viable andeffective approach for the job-shop scheduling problem.

Factors Affecting the Rent of Shops in Commercial Complexes: A Case Study of Shenzhen Shekou Sea World

The rent of shops in commercial complex reflects consumers’ preferences to some extent, and provides references for urban planning and the construction and operation of commercial complex. In this paper, Sea World Commercial Complex in Nanshan District of Shenzhen City is taken as the research object, and correlation and variability analysis on 41 groups of shop data are conducted. It is found that rent of shops in the same commercial complex is affected by location, visibility and area of outdoor stall, while the influence of shop area on rent is not obvious. Additionally, there is no significant correlation between the accessibility to traffic stations and the rent of shops in pedestrian business district.

Modified Shifting Bottleneck Heuristic for Scheduling Problems of Large-Scale Job Shops

A modified shifting bottleneck algorithm was proposed to solve scheduling problems of a large-scale job shop.Firstly,a new structured algorithm was employed for sub-problems so as to reduce the computational burden and suit for large-scale instances more effectively.The modified cycle avoidance method,incorporating with the disjunctive graph model and topological sort algorithm,was applied to guaranteeing the feasibility of solutions with considering delayed precedence constraints.Finally,simulation experiments were carried out to verify the feasibility and effectiveness of the modified method.The results demonstrate that the proposed algorithm can solve the large-scale job shop scheduling problems(JSSPs) within a reasonable period of time and obtaining satisfactory solutions simultaneously.

Prevalence and Predictors of Salmonella spp. in Retail Meat Shops in Kathmandu

A cross-sectional study was conducted from November 2008 to May 2009 to estimate the prevalence of Salmonella in retail meat shops in Kathmandu. The methods followed were ISO 18593：2004 for swab sample collection, ISO 6579：2002 for Salmonella isolation and manufacturer＇s instructions （SIFIN, Germany） for serotype identification. A questionnaire was used to collect information on some of the risk factors of shops likely to be associated with Salmonella identification. A total of 492 environmental swab samples （164 chopping board samples, 164 knife samples and 164 table samples） from 82 retail meat shops were analyzed. The prevalence of Salmonella positive shops was 40.2% （95% CI： 29-51）. The isolation rates of Salmonella from chopping boards （36.0%）, knives （32.9%） and tables （25.0%） were not significantly different （P 〉 0.05）. Retail meat shops were 1.9 times more likely to yield Salmonella in the evening （38.2%） as compared to the morning （24.4%） （P = 0.001）. S. Typhimurium （54.5%） was the most common serotype found in retail meat shops followed by S. Enteritidis （16.9%）, S. Haifa （13.6%）, S. Virchow （10.4%）, S. Agona （3.9%） and S. enterica （0.6%）. Among the risk factors examined, ＂hygiene status of shop＂, ＂type of shops＂, ＂number of person handling meats＂, ＂number of knives used＂, ＂number of kinds of meat sold＂ and ＂number of kinds of meat sold using different numbers of knives＂ were individually significantly （P 〈 0.05） associated with Salmonella contamination in the retail meat shops. After univariate analysis of these risk factors, a final logistic regression model with Salmonella yes or no category of shops as outcome variable identified four significant predictors. Odds ratios, indicating the likelihood increase of a shop to achieve Salmonella positivity status were 10.17 for multiple persons rather than a single person involved, 7.66 for open rather than closed shops, 9.44 for use of several knives rather than one knife and 5.18 for single kind of meat using several knives. The results of this investigation revealed that retail meat shops to a noticeable extent are Salmonella contaminated, with a considerable degree of cross-contamination between meats and personnel and equipment used during a day in processing of meats.

Scheduling on 2-Machine Flow Shops Considering Disturbance on Job Processing Times

In this paper the scheduling problem to minimize the expected makespan is discussed on two-machine flow shops with random disturbance on job processing times. The problem is represented by a stochastic programming model. We approximate the stochastic problem by a deterministic problem which can be solved by Johnson's rule. The estimation of approximation error is also discussed by analyzing the stochastic model and its approximate LP model.

Research on Digital Marketing Intelligence Innovation of Guangzhou’s Time-Honored Brands in the Era of Big Data

Guangzhou’s time-honored brands are the image of Guangzhou City,the historical legacy of the cultural emblems of the millennium commercial capital,the bearer of the memory of“old Guangdong”over generations,and the legends inscribed in the vast era of history.It not only carries the rise and fall of the city,but also documents the awakening,rejuvenation,and development of these“gold-lettered signboards.”In this age of big data,it is not only the expectation of the older generation,but also the responsibility of the new generation to“polish”the gold-lettered signboards of time-honored brands.“Time-honored brands”have accumulated rich and priceless knowledge from their ancestors in the vast era of business history and have profound cultural legacy.The time-honored brands that have been handed down not only allow the new generation to experience and identify with the unbounded knowledge of ancient people,but also provide economic value that can ensure the survival of future generations.However,in the market tide,the development of time-honored brands is not easy;some have even vanished.Therefore,it is imperative to take action to safeguard the development of time-honored brands,helping them to revitalize and shine once again.This paper discusses the difficulties in the development of Guangzhou’s time-honored brands and provides relevant suggestions for digital intelligence marketing of these“brands.”

Art and Print Shops

Do you enjoy art?Maybe you like to draw or color.If you want to do those things,you need supplies.You can go to an art store to buy them.You can buy colored pencils,markers or crayons.You can buy paper to draw pictures on.You can also buy coloring books.If you want to make things out of paper,you can buy colorful paper,too.Are you a painter?You can buy many different kinds of paint at an art store.

Q-Learning-Assisted Meta-Heuristics for Scheduling Distributed Hybrid Flow Shop Problems

The flow shop scheduling problem is important for the manufacturing industry.Effective flow shop scheduling can bring great benefits to the industry.However,there are few types of research on Distributed Hybrid Flow Shop Problems(DHFSP)by learning assisted meta-heuristics.This work addresses a DHFSP with minimizing the maximum completion time(Makespan).First,a mathematical model is developed for the concerned DHFSP.Second,four Q-learning-assisted meta-heuristics,e.g.,genetic algorithm(GA),artificial bee colony algorithm(ABC),particle swarm optimization(PSO),and differential evolution(DE),are proposed.According to the nature of DHFSP,six local search operations are designed for finding high-quality solutions in local space.Instead of randomselection,Q-learning assists meta-heuristics in choosing the appropriate local search operations during iterations.Finally,based on 60 cases,comprehensive numerical experiments are conducted to assess the effectiveness of the proposed algorithms.The experimental results and discussions prove that using Q-learning to select appropriate local search operations is more effective than the random strategy.To verify the competitiveness of the Q-learning assistedmeta-heuristics,they are compared with the improved iterated greedy algorithm(IIG),which is also for solving DHFSP.The Friedman test is executed on the results by five algorithms.It is concluded that the performance of four Q-learning-assisted meta-heuristics are better than IIG,and the Q-learning-assisted PSO shows the best competitiveness.

An Elite-Class Teaching-Learning-Based Optimization for Reentrant Hybrid Flow Shop Scheduling with Bottleneck Stage

Bottleneck stage and reentrance often exist in real-life manufacturing processes;however,the previous research rarely addresses these two processing conditions in a scheduling problem.In this study,a reentrant hybrid flow shop scheduling problem(RHFSP)with a bottleneck stage is considered,and an elite-class teaching-learning-based optimization(ETLBO)algorithm is proposed to minimize maximum completion time.To produce high-quality solutions,teachers are divided into formal ones and substitute ones,and multiple classes are formed.The teacher phase is composed of teacher competition and teacher teaching.The learner phase is replaced with a reinforcement search of the elite class.Adaptive adjustment on teachers and classes is established based on class quality,which is determined by the number of elite solutions in class.Numerous experimental results demonstrate the effectiveness of new strategies,and ETLBO has a significant advantage in solving the considered RHFSP.

China's E-commerce Operators Ready for Double 11 Shopping Festival

With one month until November 11,all major e-commerce platforms have started their preparations for this great event.The"Double 11"shopping festival was first initiated by Alibaba in 2009and is the world's largest online sales gala.This shopping festival is thus named due to the date of November11 and has extended from the original24 hours to several weeks in recent years.The pre-sales stage start from late October.Some new e-commerce companies like TikTok and Pinduoduo have also been involved in the event.

Correlation between psychological resilience and burnout among female employees in a shopping mall in Xi Xian new area,China:A cross-sectional survey-Retraction

In the article titled“Correlation between psychological resilience and burnout among female employees in a shopping mall in Xi Xian New Area,China:A cross-sectional survey”by Zhang Q and Liu L(J Integr Nurs 2021;3(3):117-121.doi:10.4103/jin.jin_14_21),[1]the content and results data of this article was questioned by International database(Web of Science)institution.This article was then investigated by the publisher and Journal of Integrative Nursing(JIN).