Load Planning Research Articles

Load planning in the preparation of highly qualified powerlifters in the competitive period of the macrocycle

The analysis of scientific and methodical literature confirms the fragmentary consideration of a problem of planning of loading of athletes in classic powerlifting that is connected with identification of preparation of athletes in equipped and classic divisions. The results of athletes in classic powerlifting are identical to the results of some weight categories in the equipment division. Despite the rapid dynamics of results, the scientific justification for building the training of athletes in classic powerlifting is based on the achievements of scientists in the field of weightlifting or equipment powerlifting. The purpose is to identify the features of load planning in the training of highly qualified powerlifters in the competitive period of the macrocycle. To solve this goal, we used the following research methods: analogy, analysis, synthesis, abstraction, induction, extrapolation, generalization of practical experience, analysis of documentary materials, methods of mathematical statistics. The study revealed the following patterns in load planning in the training of highly qualified powerlifters in the competitive period of the macrocycle: inverse dependence in planning the volume and intensity of the load in training, which is a gradual increase in intensity against the background of the load as you approach the main competitions; nonlinear planning of loading in microcycles in separate groups of exercises on the basis of application of big indicators of intensity of loading in one group of exercises and average and small intensities in two other groups; reducing the intensity of the load in the groups of exercises as you approach the main competitions in accordance with the number of muscle groups involved during the performance of these exercises.

Development and visualization of the computer loadıng plannıng model for the cargo aırcraft

Loading an aircraft is an extremely complex process with many variable aspects that determine the planning of each flight separately. The article is devoted to the development of an algorithm and a computer model for planning the loading of a cargo ramp aircraft in a multi-lag route. The essence of the algorithm consists in a predetermined arrangement of cargo containers relative to the cargo compartment, taking into account the general limitations of the aircraft and the priority of the cargo, which directly affects the planning of loading in a multi-lag route. The use of a visualized computer model created on the basis of the algorithm can reduce the average time of loading operations for a number of direct flights by almost 7 %, and on multi-lag flights by 12 %. Implementation of the model in the activities of an air carrier avoids a situation where certain criteria and restrictions entail sorting «manually» by all indicators, which is very time-consuming in the context of the urgency of servicing the aircraft at the airport. The visualized load planning computer model enables flight planning personnel to make faster decisions and predict additional load on other sections of the route. The successful application of the model to the airline’s operations contributes to the efficiency and safety of ground handling services. This contributes to the intensification of the use of the aircraft fleet by increasing the speed of commercial cargo handling. In the future, the computer model can serve as the basis for a rule-based expert system in order to prevent containers from being overloaded at intermediate sections of the route

Approximation of the Double Traveling Salesman Problem with Multiple Stacks

The Double Traveling Salesman Problem with Multiple Stacks, DTSPMS, deals with the collect and delivery of n commodities in two distinct cities, where the pickup and the delivery tours are related by LIFO constraints. During the pickup tour, commodities are loaded into a container of k rows, or stacks, with capacity c. This paper focuses on computational aspects of the DTSPMS, which is NP-hard. We first review the complexity of two critical subproblems: deciding whether a given pair of pickup and delivery tours is feasible and, given a loading plan, finding an optimal pair of pickup and delivery tours, are both polynomial under some conditions on k and c. We then prove a (3k)/2 standard approximation for the Min Metric k DTSPMS, where k is a universal constant, and other approximation results for various versions of the problem. We finally present a matching-based heuristic for the 2 DTSPMS, which is a special case with k=2 rows, when the distances are symmetric. This yields a 1/2−o(1), 3/4−o(1) and 3/2+o(1) standard approximation for respectively Max 2 DTSPMS, its restriction Max 2 DTSPMS(1,2) with distances 1 and 2, and Min 2 DTSPMS(1,2), and a 1/2−o(1) differential approximation for Min 2 DTSPMS and Max 2 DTSPMS.

Load Optimization using Genetic Algorithm and Decision Support System

The global trade supply chain consists of container shipment of hundreds of millions of metric tons of deadweight. With the ever-increasing demand for a freight shipment, the need of the hour is optimized freight loading pattern and plan. This scholarly paper aims to optimize the loading pattern within a container to make space for more cargo making underutilization of space inside a container almost near to obsolete. In this paper, we have surveyed research papers that the existing system uses. The proposed way out to overcome the flaws is a model which is an amalgamation of Decision Support System (DSS) and Genetic Algorithm (GA). This hybrid algorithm is first fed the container size and the number of different sizes of cargo individually. The input data will then run GA against a certain set of predefined target parameters. Upon multiple iterations, GA will generate multiple near-optimal solutions. This pool of solutions will be processed with the help of DSS to decide the optimal loading pattern. The optimal solution is fed in the form of coordinates to the Unity engine. The Unity engine will use the given coordinates to simulate a 3D optimized loading pattern inside a container. The user can see a step-by-step simulation of loading the cargo into the container where the cargo will be color-coded. This result can be stored to refer to and transport a similar cargo.

Дослідження впливу різних факторів календарного планування вантажної роботи на підвищення переробної спроможності сортувальної станціі

В статті проведено аналіз існуючого стану переробної спроможності маневрових пристроїв і наведені перспективні показники, одержувані за рахунок оптимізації планів навантаження. Показано, що одним з основних напрямків розвитку державних сортувальних станцій є перегляд основних підходів та методів планування роботи станцій. На основі проведеного дослідження впливу різних факторів календарного планування вантажної роботи надані рекомендації щодо оптимізації роботи сортувальних гірок в сортувальному парку магістральної станції.

Research and Analysis on The Identification Technology of User Group Network in Distribution Station Area

Due to frequent line reconstruction in the distribution station area, the lines between adjacent lines in the distribution station area are messy and the paths are illegible, so that it is difficult for power grid companies to obtain accurate line losses and cannot balance the load planning, which is not conducive to the station area. Local refined management and service levels have been improved. In order to solve this problem, many identification technologies for users in distribution network stations have been proposed. However, traditional identification technologies have problems such as low accuracy and poor detection failure. The most important thing is that it is difficult to demodulate and identify signals. In order to solve this problem, this paper uses an improved differential cross-correlation algorithm to demodulate and identify the signal, and the power communication technology that carries information by artificially generating small distortions of the grid voltage and current. The experimental results prove the feasibility of the method proposed in this paper. Sex and effectiveness.

Critical processor download planning device in the multiprocessor systems

The article deals with the critical multi-processor systems, which can include high-availability objects, and which performance is critical for any kind of activity. Such as a person, country, company, organization, etc. In this case, failure leads to a reduction in the system’s response time and a further decrease in its performance, which means the availability factor. Thus, the usage of software solutions to this issue is unacceptable, and therefore it is necessary to use specialized hardware for load planning.

A novel structure to model the distribution of relief items in a post-disaster situation

Purpose There is usually a considerable shortage of resources and a lack of accurate data about the demand amount in a post-disaster situation. This paper aims to model the distribution and redistribution of relief items. When the new data on demand and resources become available the redistribution of previously delivered items may be necessary due to severe shortages in some locations and surplus inventory in other areas. Design/methodology/approach The presented model includes a vehicle routing problem in the first period and some network flow structures for succeeding periods of each run. Thereby, it can produce itineraries and loading plans for each vehicle in all periods when it is run in a rolling horizon manner. The fairness in distribution is sought by minimizing the maximum shortage of commodities among the affected areas while considering operational costs. Besides, equity of welfare in different periods is taken into account. Findings The proposed model is evaluated by a realistic case study. The results show that redistribution and multi-period planning can improve efficiency and fairness in supply after the occurrence of a disaster. Originality/value This paper proposes an operational model for distribution and redistribution of relief items considering the differences of items characteristics. The model integrates two well-known structures, vehicle routing problem with pickup and delivery and network flow problem to take their advantages. To get more practical results, the model relaxes some simplifying assumptions commonly used in disaster relief studies. Furthermore, the model is used in a realistic case study.

Integrated express shipment service network design with customer choice and endogenous delivery time restrictions

Express parcel carriers offer a wide range of guaranteed delivery times in order to separate customers who value quick delivery from those that are less time but more price sensitive. To reflect the additional complexity this segmentation adds to the task of optimizing the logistics operations, we present a new model that accounts for the interplay between pricing of due times, customer decisions and the associated restrictions in the distribution process. This profit-maximizing express shipment service network design problem is solved by a heuristic solution approach that simultaneously determines the ideal set of offered delivery times, the associated pricing scheme and the load plan in order to maximize profit. High-quality solutions for realistically-sized instances are derived by a genetic-algorithm-based heuristic that exploits information of previously evaluated iterations. Using this new integrated approach, we provide insight on the potential benefit of an integrated model over sequential optimization of revenue and delivery cost. We also investigate the impact of tighter delivery due times on resource requirements and whether more granular service segmentation can be considered a profitable strategy in multimodal express parcel delivery networks.

Restoration switching analysis in the integrated architecture for distribution network operation

Distribution network restoration is a recurrent issue of interest to power industry because electric distribution grids remain vulnerable against natural disasters and customers' expectations toward the continuity of electricity service are increasing in modern society. The increasing requirement for operation efficiency has encouraged the modernization of power distribution system by implementing new technologies of control and automation and data conditioning and processing. The integrated architecture of advanced distribution and outage management systems provides situational awareness of distribution networks. Fully automated restoration takes a central role with data from the distribution state estimation for achieving the feeder loading and switching plan able to reestablish the interrupted service. In active distribution networks, restoration switching analysis moves from a multi-objective model, where operator chooses the most suitable switching plan, to a single-objective optimization model for the fully automated restoration. The numerical analysis under a real-world substation is performed in three stages taking into account, firstly, the multi-objective solution and, then, the compromise solution under load forecast and, at last, the benefits of the automatic switching operation are verified.

Integrated inbound train split and load planning in an intermodal railway terminal

In the last decades the intermodal transportation of containers has become a key component of the entire international trade system, as it allows safe and efficient intercontinental door-to-door movement of freight by combining land and sea transportation services. Intermodal railway terminals are special components of these systems that allow container traffic to be consolidated from different sources and to be transported by train over long distances. This paper addresses a practical problem faced by a major North American railway. On a daily basis, terminal operators must make several decisions such as how inbound trains are split into sequences of railcars, on which tracks these railcars are parked for loading and off-loading operations, and how the railcars are assigned to outbound blocks so as to fulfill the demand of each block. We introduce an approach that incorporates all these decisions to obtain improved solutions. In a first step, a mixed integer linear programming (MILP) model is used to create a set of patterns that specify how each inbound train is split and how the railcars are assigned to the blocks. Then, in a second step, another MILP formulation decides which patterns to use and where to park the railcars. Tests on generated benchmark instances based on realistic data from the railway indicate that our approach is able to generate good quality solutions for all instances and can be used by the company to assist decision makers in generating less costly and more efficient plans.

Using genetic algorithms for operational planning of cement mills loading

The article discusses the problem automating the construction of schedules for cement production. The necessity using a computer system for planning the loading of technological equipment is substantiated in order to develop the optimal use of available resources for the timely and high-quality execution production tasks. The essence of the problem is shown, which is to allocate resources (cement mills and produced brands of cement) the production system for a given target plan so as to exclude deviations the real plan from the target, as well as to reduce the number of mill switchings to a minimum. The formalization the task planning the loading the mills is carried out and those essential parameters of the process are given, which are selected as the initial data for solving the task planning the operation of grinding mills. The solution to the problem constructing schedules for the operation of cement mills is based on the use of a genetic algorithm, for which an implementation sequence is proposed. The results solving the problem are also presented, which confirm the correctness the chosen method and its implementation.

Intelligent Consumer Flexibility Management With Neural Network-Based Planning and Control

Optimal management of demand-side flexibility in buildings is important for properly integrating large amounts of intermittent generation from windmills and photovoltaics. This paper proposes a novel Energy Management Agent (EMA) concept that can optimize building’s energy costs with respect to external prices while at the same time allow building’s flexibility to be used via explicit demand response. The EMA combines Artificial Neural Networks (ANN) and model predictive control for modelling and optimization of building’s flexibility. It continuously manages building’s flexibility with respect to external prices and provides forecasts of the load and available flexibility for a defined time window. A proof-of-concept (PoC) of the EMA is implemented for controlling a heat pump in an apartment, located in Oulu, Finland. Two ANN-based models were implemented for modelling the energy consumption of the heat pump and the indoor temperature of the apartment. Monte Carlo Tree Search based planning and control was implemented for finding optimal control policies with the ANNs. The EMA PoC was evaluated in 16-week period between 11 November 2019 - 1 March, 2020. When compared to a fixed setpoint control strategy, the EMA achieved 14.8 % lower costs under Nord Pool spot prices for Finland. At the same time, it was also able to accurately follow the 24h load plans (NRMSE was 0.050) and activate the offered flexibilities (NRMSE was 0.074).

Study on Dose Rate on the Surface of Cask Packed with Activated Cut-off Pieces from Decommissioned Nuclear Power Plant

Background: Reactor pressure vessel (RV) with internals (RVI) are activated structures by neutron irradiation and volume contaminated wastes. Thus, to develop safe and optimized disposal plan for them at a disposal site, it is important to perform exact activation calculation and evaluate the dose rate on the surface of casks which contain cut-off pieces. Materials and Methods: RV and RVI are subjected to neutron activation calculation via Monte Carlo methodology with MCNP6 and ORIGEN-S program—neutron flux, isotopic specific activity, and gamma spectrum calculation on each component of RV and RVI, and dose rate evaluation with MCNP6. Results and Discussion: Through neutron activation analysis, dose rate is evaluated for the casks containing cut-off pieces produced from decommissioned RV and RVI. For RV cut-off ones, the highest value of dose rate on the surface of cask is 6.97 × 10-1 mSv/hr and 2 m from it is 3.03 × 10-2 mSv/hr. For RVI cut-off ones, on the surface of it is 0.166 × 10-1 mSv/hr and 2 m from it is 1.04 × 10-1 mSv/hr. Dose rates for various RV and RVI cut-off pieces distributed lower than the limit except the one of 2 m from the cask surface of RVI. It needs to adjust contents in cask which carries highly radioactive components in order to decrease thickness of cask. Conclusion: Two types of casks are considered in this paper: box type for very-low-level waste (VLLW) as well as low-level waste (LLW) and cylinder type for intermediate-level waste (ILW). The results will contribute to the development of optimal loading plans for RV and RVI cut-off pieces during the decommissioning of nuclear power plant that can be used to prepare radioactive waste disposal plans for the different types of wastes—ILW, LLW, and VLLW.

Studi Estimasi Beban Puncak Hari Libur Nasional Sistem Interkoneksi Sulselbar Menggunakan Jaringan Syaraf Tiruan Propagasi Balik

The development of population from time to time is increased and the need for electricity consumption is also increased. Simultaneously increasing the need for electric power requires the provider of electricity supply in this case PT. PLN (Persero) should deliver power effectively to consumers. To maximize the distribution of electricity to the consumer, a load planning is required. This load planning is conducted to find out how much amount of power is required by consumer. The purpose of this research is to investigate the need of power load of interconnection system of South Sulawesi and to investigate the accuracy of load planning using Artificial Neural Network (ANN) backpropagation.

Artificial intelligence‐led decision support services to reduce caregiver load related to persons with cognitive impairment

AbstractBackgroundThe number of people in the US living with cognitive impairment (including Alzheimer’s Disease and other dementia) is over 5.8M today, and is expected to increase to nearly 14M by 2050 [c.f. alz.org]. The rapidly growing population of informal caregivers is subject to high stress due to patient behavioral symptoms, increased demands on caregiver time, and lack of knowledge about new care giving tasks. Many of these tasks are complex and time consuming such as determining and coordinating services/resources for the patients, seeking information and talking with the clinical team about patient conditions and care plans, and arranging for someone to care for their charge.MethodWe hypothesize that the power of artificial intelligence (AI) technology can be harnessed to meaningfully support caregivers in time consuming, complex tasks encountered in care giving and thereby reduce their load before, during and after diagnosis. We have developed a set of ARTful (accountable, responsible, and transparent) AI services to support informal caregivers of patients with mild cognitive impairment who are being diagnosed and treated at a hospital Memory Clinic. Barriers to adoption of AI technology services include usability (as defined in the System Usability Scale), acceptability (fear of AI) and experience (digitally unprepared) on the part of patient/caregiver pairs.ResultIn this paper, we present case studies covering service onboarding, caregiver exploration and patterns of use of the AI technology, and initial assessment of its impact on adherence to care plans and on caregiver burden. Preliminary findings indicate that well‐thought out AI‐led solutions can reduce caregiver load and increase care plan adherence. A double‐blind study is planned to quantitatively assess impact as measured by scores on the Oberst Caregiver Burden Scale.ConclusionA demonstration of the effectiveness of this technology in reducing caregiver load will lead to a scalable, cost‐effective solution that raises the standard of current practices in neurodegenerative care, and leads to improved health outcomes.

A New Convolutional Neural Network-Based System for NILM Applications

Electrical load planning and demand response programs are often based on the analysis of individual load-level measurements obtained from houses or buildings. The identification of individual appliances’ power consumption is essential, since it allows improvements, which can reduce the appliances’ power consumption. In this article, the problem of identifying the electrical loads connected to a house, starting from the total electric current measurement, is investigated. The proposed system is capable of extracting the energy demand of each individual device using a nonintrusive load monitoring (NILM) technique. An NILM algorithm based on a convolutional neural network is proposed. The proposed algorithm allows simultaneous detection and classification of events without having to perform double processing. As a result, the calculation times can be reduced. Another important advantage is that only the acquisition of current is required. The proposed measurement system is also described in this article. Measurements are conducted using a test system, which is capable of generating the electrical loads found on a typical house. The most important experimental results are also included and discussed in the article.

Sustainable Ship Loading Planning for Prefabricated Products in the Construction Industry

This paper focuses on sustainable transportation of prefab products from factories to construction sites by ship. Since the transportation cost for all the prefab products of a construction site is mainly dependent on the number of cargo holds used on ships, a loading plan for prefab products that minimizes the number of holds required is highly desirable. This paper is therefore devoted to the development of an optimal loading plan that decides which prefab products are loaded into each cargo hold and how to pack these prefab products into the holds so that as few holds as possible are used. We formulate the problem as a large-scale integer optimization model whose objective function is to minimize the total number of cargo holds used and whose constraints represent the cargo hold capacity limits. We develop a heuristic to solve the problem and obtain a high-quality solution. We have tested the model and algorithm on a case study that includes 20 prefab products. We find that different cargo holds carry prefab products that have quite different densities. Moreover, the orientations of many prefab products are different from their default orientations. The results demonstrate the applicability of the proposed model and algorithm.

The Value of Limited Flexibility in Service Network Designs

Less-than-truckload carriers rely on the consolidation of freight from multiple shippers to achieve economies of scale. Collected freight is routed through a number of transfer terminals at each of which shipments are grouped together for the next leg of their journeys. We study the service network design problem confronted by these carriers. This problem includes determining (1) the number of services (trailers) to operate between each pair of terminals and (2) a load plan, which specifies the sequence of transfer terminals that freight with a given origin and destination will visit. Traditionally, for every terminal and every ultimate destination, a load plan specifies a unique next terminal. We introduce the [Formula: see text]-alt model, which generalizes traditional load plans by allowing decision makers to specify a desired number of next-terminal options for terminal–destination pairs using a vector [Formula: see text]. We compare a number of exact and heuristic approaches for solving a two-stage stochastic variant of the [Formula: see text]-alt model. Using this model, we show that, by explicitly considering demand uncertainty and by merely allowing up to two next-terminal options for terminal–destination pairs in the load plans, carriers can generate substantial cost savings that are comparable to the ones yielded by adopting load plans that allow for any next terminal to be a routing option for terminal–destination pairs. Moreover, by using these more flexible load plans, carriers can generate savings on the order of 10% over traditional load plan designs obtained by deterministic models.

DEVELOPMENT AND USE OF IT SOLUTIONS IN LOGISTICS

Анотація. Безперервний рух до досконалості вимагає постійного контролю і вдосконалення управлінських рішень на підприємстві. Досягти окресленої мети і завдань можливо на основі ІТ-технології для потреб логістики. ІТ-компанії (360data, Alpega, C3 Solutions, CyberLogitec, Data2Logistics та ін.) зосереджують свою увагу на вирішенні як окремих, так і комплексних завдань (планування завантаження, оптимізація, закупівлі, швидкість та ставки, зворотна логістика, маршрутизація і планування, система управління транспортом тощо) логістичних підприємств. Це дає змогу впроваджувати та експлуатувати ІТ-рішення в області ланцюгів поставок, логістики, вертикальної спеціалізації, базової вартості, сторонньої логістики та додаткових рішень. На сьогодні питання підвищення ефективності логістичних процесів вимагають активних дій з боку керівництва компаній, тому їхня конкурентоспроможність, передусім, залежить від своєчасності реагувати на глобальні тренди і виклики в області ІТ-технологій. ІТ-розробники, як засвідчили дослідження, найбільше концентрують свою увагу на розв’язанні проблем постачальників транспортних послуг — на них надає понад 90 % усіх респондентів. Також потрібно відмітити, що понад 80 % ІТ-рішень у вертикальній спеціалізації зосереджено в галузі сільського господарства щодо виробництва, транспортування та гуртової торгівлі. Попри зазначені досягнення, менше ніж 40 % компаній використовують технологію для контролю продуктивності ланцюгів поставок. У зв’язку зі зростанням складності відправлення вантажовідправниками вантажів клієнтам, багато компаній звертаються до допомоги так званої 3PLs (third-partylogistics). Проведені дослідження показали, що понад 80 % усіх вантажовідправників використовують 3PLs, що допомагає їм підвищити якість обслуговування клієнтів. Серед компаній, які впроваджують і використовують досягнення ІТ-технологій у своїй логістичній діяльності, можна виділити Maersk, Schneider, LufthansaCargo, SAS CargoGroup A/S, AsstrA та ін. Зазначені ІТ-рішення дали таким компаніям можливість більш ефективно контролювати і координувати доставку вантажів, інтегрувати інтерфейси вантажовідправника та клієнта в єдину мережу, оптимізувати роботу власних підрозділів, знизити логістичні витрати тощо. Це також підтверджується й тим фактом, що понад 60 % усіх старших керівників, які причетні до роботи транспорту на підприємствах, відчули суттєві позитивні зміни глобальних перетворень. Ключові слова: інновації, ІТ-технології для потреб логістики, ІТ-рішення, логістичні компанії, логістичні послуги. Формул: 0; рис.: 0; табл.: 2; бібл.: 21.