Mid-term Planning Research Articles

RescuePY: Simulation-Based Rescue Response Impact Assessment

Mobility in metropolitan regions is changing. The distribution of space in cities, the design of transport modes, and the organization of mobility are being re-thought. However, no matter the changes and innovations on the way to a more sustainable future, essential constants must be upheld: In the event of minor, regionally limited emergencies, medical assistance must reach those in need quickly. When dealing with large-scale emergencies, the ability to evacuate the area promptly must be ensured. The impact analysis of mobility innovations on emergency services within urban areas so far has been based purely on empirical observations using existing data. Currently, it is only possible to analyze what-if considerations in a limited way. Nevertheless, due to the increasingly rapid changes in mobility, a comprehensive and interlinked analysis will be necessary. This is the key contribution of rescuePY: rescuePY is a simulation suite based on the mesoscopic and microscopic simulation environment hybridPY. It allows holistic and microscopic transport modeling of rescue infrastructure to quantify the impact of the mobility transition towards higher sustainability on the performance of rescue services. The main features of this software are: Rescue system assessment for strategic, long-term planning Mobility-influence studies for operative, mid-term planning Activity-based urban evacuation modeling The capabilities of rescuePY are demonstrated by two applications: a simulation- based, mesoscopic system analysis of emergency services in Munich compared to real-world data and microscopic modeling of emergency vehicles (EMVs) in different road architectures. Ongoing developments aim to improve the evaluation methodology for the aggregated impact analysis of mobility innovations on rescue response services.

Planning and Management of Village Funds for The Development of Cunca Wulang Tourism Village

This study aims to identify and understand the system of planning and managing village funds for the development of tourist villages in Cunca Wulang. This type of research is descriptive type using primary and secondary data collected using observation, interview and documentation techniques. Data collection techniques were carried out by direct question-and-answer interviews with research informants, observations and interviews. The results of the research show that the planning and management of village funds is carried out in two stages by the Cunca Wulang village government. The first stage of village fund planning and management begins with the establishment of a village mid-term planning and management team (RPJMDesa). Formation of the RPJMDes planning team, preparation of the RPJMDesa and RKPDes documents so that they become the APBDes up to the preparation of the APBDes. In the second stage, the Cunca Wulang village government for tourism development has a tourism planning stage which is the most basic stage for the development of a tourist village. This planning stage involves the community in preparing plans so that the community can find out how to develop existing nature tourism, besides that they can feel the impact of the existence of a tourism village on the environment around the tour.

A robust fuzzy-stochastic optimization model for managing open innovation uncertainty in the ambidextrous supply chain planning problem

This paper studies the effect of the open innovation concept in the product design process and supply chain master planning. Complex uncertainties caused by using outbound resources within co-design processes, financial challenges between the collaborating parties, and integrating outbound innovative designs with supply chain tactical planning problem are taken into account. To this end, a robust fuzzy-stochastic optimization model is proposed which can integrate the product design with the main activities of a multi-product supply chain. The proposed model is able to cope with different type of uncertainties including random, epistemic and deep uncertainties. Integrating the financial and physical flows, using a novel pricing mechanism, and considering the outside-in innovations in the product design process are the outstanding contributions of the proposed model. Furthermore, to cover both the short-term and long-term success criteria, ambidexterity of the studied supply chain is taken into account via two conflicting explorative and exploitive objectives. Results indicate the superiority of the presented model and its ability in supporting managerial decisions in the mid-term planning process.

The Planned System of Cuba in 1970—1975 in the Context of Joining the COMECON

The paper analyzes changes within the planning system of the Cuban Republic that took place in the context of changing methodological base of planning while entering the Council for Mutual Economic Assistance (Comecon). The end of 1960s was marked by a radicalization of the methods of socialist construction: the system of economic register was applied and diminished the role of the category of value. This led to an economic imbalance, loss of control over the costs of production, deterioration of motivation to labour, etc. In addition, the plan of 10 million tons of sugar production in 1970 was not achieved. These factors prompted the Cuban leadership to reconsider the planning methodology and the development strategy, and to rely heavily on the experience of the USSR. Thus, the Soviet Gosplan experts started consulting their Cuban colleagues from the Central planning committee to a greater extent. However, sometimes there was misunderstanding between the parties, which is revealed in the conversations between the Soviet Gosplan head N. Baybakov and Cuban leader F. Castro. Carlos Rafael Rodríguez played a significant role in political economy diplomacy, and gave a speech as a representative of Cuba at the XXVI Comecon session when the country was accepted to the organization. Entering Comecon spurred the process of changes within the Cuban economic policy: the category of value recuperated its significance within the planning system, new annual plans were based on the value indicators and the input-output models. The midterm planning was also reintroduced due to 5-year plans preparation. Cuba integrated the mechanism of plan coordination with the Comecon countries, while the USSR continued to be its most important partner. Nonetheless, the process was slow: the 1971—1975 five-year plan had not been connected to the Comecon mechanism of plan coordination. Cuba insisted on a special attitude due to its low level of development. Cuban economy reconfiguration under the influence of planning mechanisms of Comecon countries favored consolidation of the new System of planning and direction of the economy approved by the decisions of the first congress of the Communist party of Cuba in 1975.

A Fuzzy Prescriptive Analytics Approach to Power Generation Capacity Planning

This study examines the long-term energy capacity investment problem of a power generation company (GenCo), considering the drought threat posed by climate change in hydropower resources in Turkey. The mid-term planning decisions such as maintenance and refurbishment scheduling of power plants are also considered in the studied investment planning problem. In the modeled electricity market, it is assumed that GenCos conduct business in uncertain market conditions with both bilateral contracts (BIC) and day-ahead market (DAM) transactions. The problem is modeled as a fuzzy mixed-integer linear programming model with a fuzzy objective and fuzzy constraints to handle the imprecisions regarding both the electricity market (e.g., prices) and environmental factors (e.g., hydroelectric output due to drought). Bellman and Zadeh’s max-min criteria are used to transform the fuzzy capacity investment model into a model with a crisp objective and constraints. The applicability of methodology is illustrated by a case study on the Turkish electric market in which GenCo tries to find the optimal power generation investment portfolio that contains five various generation technologies alternatives, namely, hydropower, wind, conventional and advanced combined-cycle natural gas, and steam (lignite) turbines. The results show that wind turbines with low marginal costs and steam turbines with high energy conversion efficiency are preferable, compared with hydroelectric power plant investments when the fuzziness in hydroelectric output exists (i.e., the expectation of increasing drought conditions as a result of climate change). Furthermore, the results indicate that the gas turbine investments were found to be the least preferable due to high gas prices in all scenarios.

An Experimental Machine Learning Approach for Mid-Term Energy Demand Forecasting

In this study, a neural network-based approach is designed for mid-term load forecasting (MTLF). The structure and hyperparameters are tuned to obtain the best forecasting accuracy one year ahead. The suggested approach is practically applied to a region in Iran by the use of real-world data sets of 10 years. The influential factors such as economic, weather, and social factors are investigated, and their impact on accuracy is numerically analyzed. The bad data are detected by a suggested effective method. In addition to load peak, the 24-hours load pattern is also predicted, which helps for better mid-term planning. The simulations show that the suggested approach is practical, and the accuracy is more than 95%, even when there are drastic weather changes.

Analysis of commonly used scheduling models for multistage biopharmaceutical processes

AbstractSeveral works have been reported in the literature over the past two decades to schedule a multiproduct facility in the biopharmaceutical industry. The present work attempts to analyze a few commonly used scheduling models, based on different time representations, for midterm planning or long‐term scheduling of multistage, multiproduct biopharmaceutical facilities for multiperiod demand. Several model inconsistencies/limitations in the published literature and in the reported Gantt charts, such as (i) real‐time storage violation, (ii) early product delivery, (iii) inadequate mapping of upstream and downstream tasks, (iv) no initial setup time, and (v) incomplete sequencing/modelling of storage tasks, thus (iv) overestimating the reported objective values in their results, are identified. Accordingly, one of the unit‐specific‐event‐based literature models is improved in this work to address these limitations. An improved model is proposed with enhanced/new features such as modified material balances, proper sequencing of storage based on storage bypassing allowed for intermediates and bypassing not allowed for products, modified shelf‐life constraints, initial setup time constraints, and updated bounds on storage, giving better results compared to the published literature models.

Adaptive ensemble models for medium-term forecasting of water inflow when planning electricity generation under climate change

Medium-term forecasting of water inflow is of great importance for small hydroelectric power plants operating in remote power supply areas and having a small reservoir. Improving the forecasting accuracy is aimed at solving the problem of determining the water reserve for the future generation of electricity at hydroelectric power plants, taking into account the regulation in the medium term. Medium-term regulation is necessary to amplify the load in the peak and semi-peak portions of the load curve. The solution to such problems is aggravated by the lack of sufficiently reliable information on water inflow and prospective power consumption, which is of a stochastic nature. In addition, the mid-term planning of electricity generation should consider the seasonality of changes in water inflow, which directly affects the reserves and the possibility of regulation. The paper considers the problem of constructing a model for medium-term forecasting of water inflow for planning electricity generation, taking into account climatic changes in isolated power systems. Taking into account the regularly increasing effect of climate change, the current study proposes using an approach based on machine learning methods, which are distinguished by a high degree of autonomy and automation of learning, that is, the ability to self-adapt. The results showed that the error (RMSE) of the model based on the ensemble of regression decision trees due to constant self-adaptation decreased from 4.5 m3/s to 4.0 m3/s and turned out to be lower than the error of a more complex multilayer recurrent neural network (4.9 m3/s). The research results are intended to improve forecasting reliability in the planning, management, and operation of isolated operating power systems.

Optimizing the Supply Chain in a Fuel Process Industry

The Supply Chain Improvement (SCO) project is being introduced by KNPC, which recognises the major business advantages of improved hydrocarbon supply chain efficiency. The objectives of this work is to strengthen, optimise, and integrate supply scheduling and processes not just at stage of enterprise, but also throughout the entire KNPC framework. This is expected to lead to an improvement in the company's bottom line and facilitate the management of business operations at the highest level of efficiency, agility and profitability. In ever changing market conditions and globally competitiveness, it is necessary that raw material supply storage and product delivery were carried out at the lowest possible time and efficiency. Otherwise export oriented refinery like KNPC cannot remain in business with profit. KNPC has therefore embarked on ambitious multi-year operational excellence programs aimed at enhancing its operations and business processes that include short / mid-term planning, scheduling, accounting for growth, inventory management, and performance management. The aim is to achieve top-quartile financial results by accessing new value streams, encapsulating business processes of best practice and motivating employees of businesses to work in a collaborative atmosphere within the global and cross-functional business cycle to make smarter, quicker and more competitive choices.

A New Location and Routing Model for Cross-Docking of Fresh Produce

Traditional fresh produce logistics involve long transportation times and high loss rates. Cross-docking systems can significantly improve these issues but bring the challenge of mid-term planning in which vehicles have to be synchronized promptly at the selected cross-docks. This study proposes a new location and routing model for the cross-docking of fresh produce. Exact solutions of small-scale cases show that the model can greatly reduce the transportation time and loss rate. For real-world, large-scale cases, a greedy and biogeography-based optimization algorithm (G-BBO) is devised and tested to obtain near-optimal solutions within a reasonable time.

Levelling crane workload in multi-yard rail-road container terminals

In modern rail-road container terminals, container transshipment between trains and trucks is carried out by large gantry cranes that span over rail tracks and road lanes. Prior optimization approaches have mainly focused on the short-term scheduling of these crucial transshipment resources. In this work, we focus on a midterm planning level that assigns inbound trains to yard tracks such that trains can be serviced by yard resources on schedule. This planning task is especially crucial in larger terminal settings which comprise more than a single yard, which is increasingly typical in growing intermodal networks. We describe the planning situation we encountered at a large rail-road terminal in Germany and propose a mixed-integer model formulation that captures the core of the decision problem. Further, we carry out a complexity analysis of problem variants and develop a heuristic solution procedure in a simulated annealing framework based on these structural insights. The approach is tested in a comprehensive computational study which demonstrates the viability of the approach to solve instances of real-world size.

PECULIARITIES OF MID-TERM PLANNING OF PUBLIC FINANCE IN UZBEKISTAN

The article describes preconditions and specifics of transition to mid-term planning of the state budget in the Republic of Uzbekistan. It generalizes successful international experience of targeted budgeting program. It proves that the advantages of mid-term budget planning, first of all, include stabilization of fiscal policy and macroeconomic situation in whole, as it means public awareness of government policy for several years ahead, reduction of uncertainty and risks for business, and for foreign investors and international rating agencies it allows to assess the level of capital investment risks and ultimately, serves for improvement of investment environment, raise life standard of the population

Risk-Based Procurement Strategy for Electricity Retailers: Different Scenario-Based Methods

In mid-term planning, the objective of an electricity retailer is to procure the electricity energy to supply its demands, while efficient control of the financial risks under uncertainties is as vital as maximizing profit. To meet these challenges, this paper proposes and compares different stochastic-based risk measures including minimax regret (MMR), chance-constrained (CC), and conditional value-at-risk (CVaR) criteria, which are useful tools for assessing the risk levels, considering whether a retailer is a risk-taking or a risk-averse participant. To obtain an optimal procurement strategy, robust versions of implemented approaches are applied. To show the real performance of the proposed procurement solutions, postoptimization procedures with different price behaviors are performed to carry out experimental results on the basis of realistic data. The results show that for the same robustness degree of strategy, CVaR is less conservative than MMR and CC is less conservative than CVaR.

Mid-term Scenario Generation for Wind Power Using GAN with Temporal-correlation Enhancement Block

Under the background of increasing renewable energy penetration and rigid demand for midterm generation planning, the accurate expression of wind power uncertainty becomes more and more important. Firstly, this paper analyses the problem of scenario generation models based on traditional Generative Adversarial Networks(GAN), point that the fluctuation of scenarios that it generated usually deviates greatly from the real one. And further proposes a convolutional structure, that called Temporal-correlation Enhancement block (TE block), which can solve the aforementioned problem by enhance the temporal correlation perception ability of convolutional layers. Then, the problems of traditional conditional Wasserstein GAN-Gradient Penalty(WGAN-GP) in mid-scale scenario generation are discussed, and a conditional WGAN-GP scenario generation model that is suitable for mid-term scenario generation is presented. This model-free non-parametric model can generate a large number of realistic wind scenarios efficiently according to the given conditions. In order to validation, we use the data collected in a province in northern China to train the model in the Case Study part, and compare it with the traditional model. Result shows the fluctuation distribution deviation problem is improved obviously on the model with TE block, and in the comparison of auto-correlation coefficient, the proposed model also outperform the traditional model. This verifies the superiority of the proposed model in temporal expression ability compared with the traditional model, as well as the feasibility of the mid-term wind scenario generation.

Planning and control frameworks of the future

Since the 1970s, multiple planning and control frameworks have been introduced. The current digitalisation of the manufacturing industry, with all its Industry 4.0 related technologies, will have major implications on manufacturing logistics, and may change how manufacturing companies plan and control their production. In this paper, we discuss the effects of the developments in planning frameworks and technologies on different factors that constitute planning and control. These are the balance between human and automated planning, the influence on mid-term planning due to improved forecast accuracy, the influence of real-time information on short-term planning, horizontal and vertical integration and the impact on supply chain performance. The application of new technologies will lead to changes in all of these factors that cannot be fully captured by current planning and control frameworks. These factors need to be integrated into future frameworks in order to structure future research into planning and control.

IDENTIFICATION OF A CYCLICAL COMPONENT IN THE\r\nSOCIO-ECONOMIC DEVELOPMENT OF AZERBAIJAN

Ponte Academic JournalOct 2020, Volume 76, Issue 10 ECONOMETRIC ANALYSISOF AZERBAIJAN\'S GDP USING SINGULAR SPECTRAL ANALYSIS (SSA)Author(s): Esmira AhmadovaJ. Ponte - Oct 2020 - Volume 76 - Issue 10 doi: 10.21506/j.ponte.2020.10.16 Abstract:This article focuses on a brief critical analysis of the theory of Singular Spectrum Analysis and the problem of distinguishing cyclic components from a general dynamics of economic situation. As a solution to this problem the asynchronous harmonic analysis algorithm based on spectrum analysis and decomposition filtering algorithm has been proposed. This research is based on fundamental works by foreign scientists and research workers. The aim of this research is to identify and evaluate the cyclic component and prospects of social and economic development of Azerbaijan based on the analysis of the most important GDP indicator. As a result of the research, several economic models have been designed and important cyclic dependencies have been identified. Also, an econometric analysis of models with relevant conclusions has been performed. Calculations and graphs have been made by free software, i.e. the statistical environment R, which is one of the most dynamically developing programs in its class. In the course of the study, the main parameters, general trends, seasonal and cyclical components of Azerbaijan's GDP for the period of 22 years, between 1997 to 2019 have been identified. The comprehensive econometric tests carried out during the research showed that the designed econometric models correspond to all basic ideas of econometric analysis including the conditions of specification, parameterization and verification, and prove to be reasonable for the real economic situation in the country. The findings of the research, with regard to their practical significance, can be successfully applied to analyse and predict the socio-economic development potential during the diversification of the economy of Azerbaijan. The results, suggestions and recommendations obtained in this research can be used in shortterm and mid-term planning of the main indicators of social and economic development of Azerbaijan. Download full text:Check if you have access through your login credentials or your institution Username Password

Methodological bases of estimating the efficiency of organizational and economic mechanism of regulatory policy in agriculture

Ukrainian agriculture creates 12-14% of GDP. Ensuring the conditions for sustainable economic development implies the use of adequate mechanisms for regulating economic processes by the government. In the process of formation and implementation of the organizational and economic mechanism of regulatory policy, a system of indicators plays an important role in assessing the impact of such policy on the participants, monitoring and, in case of the deviation from planned results, adjusting regulatory measures. This research analyzes and systematizes the indicators that determine the organizational and economic mechanism of regulatory policy effectiveness in agriculture. The systematization of indicators to evaluate the organizational and economic mechanism of regulatory policy effectiveness in agriculture has allowed substantiating the methodological principles of its integrated assessment. Application of the proposed methodological approach to assessing the organizational and economic mechanism of regulatory policy effectiveness in agriculture in Ukraine was performed during 2010, 2016-2017 period. It revealed slow progress in the organizational and economic mechanism of regulatory policy efficiency during the investigated period. This result is primarily attributed to the lack of purposeful, systematic change management, the lack of mid-term planning, the strictness of most programs, imperfect financial instruments of the organizational and economic mechanism, and procedures for application.

An exploratory study on improvement of integrated logistics support (ILS) for military field equipment and materials in ROK (Republic of Korea) military

The operational maintenance areas (including maintenance budget preparation, creation cost, maintenance equipment, repair parts, and tool supply) are not sufficiently reflected in the total life cycle for acquiring and powering the weapons system, thereby reducing combat readiness and increasing operational maintenance costs. As the speed of development of the technology is accelerating, but equipment and parts in power-generating operation become obsolete, resulting in disruption to the operation of equipment and supplies at the field, the need for the establishment of a comprehensive military water support (ILS) system that is analyzed and reflected in the acquisition phase is increased. This study is required from the perspective of the total life cycle of electric power equipment and materialsThe purpose of the Chapter is to develop a realistic and efficient comprehensive military water support (ILS) development plan for stable combat capability by improving the operational disconnect and the lack of integrated comprehensive water support (ILS) management due to changes in the performance institutions during the raising, acquisition and operation maintenance stages. The establishment of a comprehensive military water support (ILS) system for field powering equipment and supplies will be reflected in decision-making between acquisitions and the results of this study can be utilized as basic data for mid-term planning and budgeting.

The GridKa Tape System: status and outlook

Tape storage is still a cost effective way to keep large amounts of data over a long period of time and it is expected that this will continue in the future. The GridKa tape environment is a complex system of many hardware components and software layers. Configuring this system for optimal performance for all use cases is a non-trivial task and requires a lot of experience. We present the current status of the GridKa tape environment, report on recent upgrades and improvements and plans to further develop and enhance the system, especially with regard to the future requirements of the HEP experiments and their large data centers. The short-term planning mainly includes the transition from TSM to HPSS as the backend and the effects on the connection of dCache and xrootd. Recent changes of the vendor situation of certain tape technologies require a precise analysis of the impact and eventual adaptation of the mid-term planning, in particular with respect to scalability challenge that comes with HL-LHC on the horizon.

Hot strip mill production planning and sequencing

Production planning and sequencing in hot strip mill (HSM) process consists of decision making about three important issues: assigning the orders to slabs, building up programs from the slabs, and sequencing the programs on rolling machines. In contrast to earlier investigations that mostly focus on one of these issues, a comprehensive mathematical model where considerations for both mid and short term planning horizons are simultaneously taken into account is presented to formulate the whole problem. A greedy algorithm is then presented to solve the model in a reasonable amount of time and used for planning in Mobarakeh Steel Company (MSC), the biggest steel enterprise in the Middle East. Computational experiments demonstrate that the proposed method substantially increases the productivity in MSC by decreasing the total tardiness of orders, unsupplied demands of products, setup times and optimally utilising the lifespans of rollers.