Structure Optimization of Mixed-Speed Train Traffic for Cyclic Timetable: Model and Algorithm Development

Trains can be optimally spread over the period of the cyclic timetable. By integrating sequencing issue with headway time together, this paper studies the structure optimization of mixed-speed train traffic for a cyclic timetable. Firstly, by taking it as a job-shop problem with sequence-dependent setup times on one machine, in the type of infinite capacity resource with headway (ICR + H), the problem is transformed to alternative graph (AG) and then recast to the mixed-speed train traffic planning (MSTTP) model. For the multiobjective in MSTTP, three indicators are optimized, i.e., heterogeneity, cycle time, and buffer time, which correspond to diversity of train service toward passenger, capacity consumption of rail network, and stability of train operation, respectively. Secondly, the random-key genetic algorithm (RKGA) is proposed to tackle the sequence and headway simultaneously. Finally, RKGA is coded with visual studio C# and the proposed method is validated with a case study. The rail system considered is a line section encompassing a territory of 180 km with 15 mixed-speed trains in each cycle of the timetable. Results indicate the comprehensively balanced train plan for all stakeholders from random variations of train sequence and headway time. Both the quantitative proportion of heterogeneity/homogeneity (e.g., 2.5) about the optimized distribution of the mixed train traffic and the link between train headway time and the sequence for each traffic scenario are found. All the findings can be used to arrange the mixed-speed train traffic more scientifically.

The Ways to Improve the Efficiency of Agricultural Enterprises

In the modern world a person strives for an industrial society more and more, accumulating power and trying to enclose them in one machine that would perform several operations in one pass over the field surface. So there are implements performing tillage with application of fertilizers or soil cultivation with simultaneous planting and application of fertilizers. Using such implements allows to reduce costs for further cultivation of crops. However, the stake placed on soil preparation and application of fertilizers can not always give the desired effect without due attention to the seed material and technical maintenance. That is why seedbed preparation, the seed material and machines are the main problems of high technology society.

One-Machine Scheduling with Time-Dependent Capacity via Efficient Memetic Algorithms

This paper addresses the problem of scheduling a set of jobs on a machine with time-varying capacity, with the goal of minimizing the total tardiness objective function. This problem arose in the context scheduling the charging times of a fleet of electric vehicles and it is NP-hard. Recent work proposed an efficient memetic algorithm for solving the problem, combining a genetic algorithm and a local search method. The local search procedure is based on swapping consecutive jobs on a C-path, defined as a sequence of consecutive jobs in a schedule. Building on it, this paper develops new memetic algorithms that stem from new local search procedures also proposed in this paper. The local search methods integrate several mechanisms to make them more effective, including a new condition for swapping pairs of jobs, a hill climbing approach, a procedure that operates on several C-paths and a method that interchanges jobs between different C-paths. As a result, the new local search methods enable the memetic algorithms to reach higher-quality solutions. Experimental results show significant improvements over existing approaches.

Scalable Fog Computing Orchestration for Reliable Cloud Task Scheduling

As Internet of Things (IoT) and Industrial Internet of Things (IIoT) devices are becoming increasingly popular in the era of the Fourth Industrial Revolution, the orchestration and management of numerous fog devices encounter a scalability problem. In fog computing environments, to embrace various types of computation, cloud virtualization technology is widely used. With virtualization technology, IoT and IIoT tasks can be run on virtual machines or containers, which are able to migrate from one machine to another. However, efficient and scalable orchestration of migrations for mobile users and devices in fog computing environments is not an easy task. Naïve or unmanaged migrations may impinge on the reliability of cloud tasks. In this paper, we propose a scalable fog computing orchestration mechanism for reliable cloud task scheduling. The proposed scalable orchestration mechanism considers live migrations of virtual machines and containers for the edge servers to reduce both cloud task failures and suspended time when a device is disconnected due to mobility. The performance evaluation shows that our proposed fog computing orchestration is scalable while preserving the reliability of cloud tasks.

A Review of Machine Translation Tools: The Translation’s Ability

The objective of the research is to review the ability of online machine translator tools includes Google Translate (GT), Collin Translator (CT), Bing Translator (BT), Yandex Translator (YT), Systran Translate (ST), and IBM Translator (IT). This research applies descriptive qualitative. The documentation was used in this study. The result of the analysis shows that the translation results are different, both from the style of language and the choice of words used by each machine translation tool. Thus, directly or indirectly, whether consciously or not, each translation machine carries its characteristics. Machine translation technology cannot be separated from the active role of humans. In other words, it will always be the best choice for users to rely on expert translation rather than machine translation. But no machine translator can be as accurate as human skills in producing translation products. In particular, the field of translation is also concerned with machine translation to support the performance of translators in analyzing the diction used as an element of language. In this regard, it needs to be underlined that the existence of machine translation is an additional facility in the world of translation, not as the main means of translation because the sophistication of the machine will not be able to match the flexibility of the human brain's cognitive abilities in adjusting the translation results according to the existing context. Accurate translation is sometimes subjective, relatively often temporal. Therefore, it is permissible for translating by more than one machine translator

System introduction and evaluation of the first Chinese chest EIT device for ICU applications

Chest electrical impedance tomography (EIT) is a promising application which is used to monitor the ventilation and perfusion of the lung at the bedside dynamically. The aim of the study was to introduce the first Chinese made chest EIT device for ICU application (Pulmo EIT-100). The system design of the hardware and software was briefly introduced. The performance of the system was compared to PulmoVista 500 (Dräger Medical) in healthy volunteers. The EIT system Pulmo EIT-100 consists of impedance measurement module, power supply module, PC all-in-one machine, medical cart and accessories. The performance of the system current source and voltage measurement unit was tested. A total of 50 healthy lung volunteers were prospectively examined. Subjects were asked to perform repetitive slow vital capacity (SVC) maneuvers with a spirometer. EIT measurements were performed in the following sequence during each SVC with: (1) Pulmo EIT-100, (2) PulmonVista500, (3) Pulmo EIT-100 and (4) PulmonVista500. Linearity and regional ventilation distribution of the reconstructed images from two devices were compared. The output frequency stability of the current source was 2 ppm. The amplitude error within one hour was less than 0.32‰. The output impedance of the current source was about 50kΩ. The signal-to-noise ratio of each measurement channel was ≥ 60 dB. For fixed resistance measurements, the measured values drifted about 0.08% within one hour. For human subjects, the correlations between the spirometry volume and EIT impedance from two devices were both 0.99 ± 0.01. No statistical significances were found in the parameters investigated. The repeatability (variability) of measures from the same device was comparable. Our EIT device delivers reliable data and might be used for patient measurement in a clinical setting.

Empowering the configuration-IP: new PTAS results for scheduling with setup times

Integer linear programs of configurations, or configuration IPs, are a classical tool in the design of algorithms for scheduling and packing problems where a set of items has to be placed in multiple target locations. Herein, a configuration describes a possible placement on one of the target locations, and the IP is used to choose suitable configurations covering the items. We give an augmented IP formulation, which we call the module configuration IP. It can be described within the framework of n-fold integer programming and, therefore, be solved efficiently. As an application, we consider scheduling problems with setup times in which a set of jobs has to be scheduled on a set of identical machines with the objective of minimizing the makespan. For instance, we investigate the case that jobs can be split and scheduled on multiple machines. However, before a part of a job can be processed, an uninterrupted setup depending on the job has to be paid. For both of the variants that jobs can be executed in parallel or not, we obtain an efficient polynomial time approximation scheme (EPTAS) of running time $$f(1/\varepsilon )\cdot \mathrm {poly}(|I|)$$ f ( 1 / ε ) · poly ( | I | ) . Previously, only constant factor approximations of 5/3 and $$4/3 + \varepsilon $$ 4 / 3 + ε , respectively, were known. Furthermore, we present an EPTAS for a problem where classes of (non-splittable) jobs are given, and a setup has to be paid for each class of jobs being executed on one machine.

ANALISIS PENGENDALIAN KUALITAS DENGAN MENGGUNAKAN METODE LEAN SIX SIGMA DI PT. XYZ

XYZ is a company that produces Medical Devices. One of the products produced is 16x16 hydrophilic sterile gauze. One of the factors that affect the quality of a product is the presence of defects in the product and waste which results in a longer lead time for a product. The investigative stages used in this study are using tools: seven tools, Big Picture Mapping, Value Stream Analysis (VALSAT) and then analyzing the causes of defects using the Ishikawa diagram (fishbone chart) where the output of this study is a proposed improvement using the FMEA method ( Failure Mode Effect and Analysis) to eliminate defects and waste that occur. Based on the research results, it is known that the type of waste identified by the calculation of Value Stream Activity and obtained Value Added with a percentage of 84.4%, Non Value Added by 1.0% and Necessary Non Value Added by 14.5%. From the results of production output in December 2019 to November 2020 amounting to 2,650,200 boxes, the number of defects is 1,316 boxes with an average sigma level of 5.16, while in FMEA it is known that the largest defects are spots with an RPN value of 504 and a suggestion for improvement is to place Experienced operators who have gone through the recruitment and training stages on superior qualifications on one machine according to their skills who understand SOPs and operators are given good comfort in the production process. Keywords: Lean Six Sigma, Seven Waste, DMAIC, FMEA, kasa steril hidrofil 16x16.