Competitive Problem Research Articles

The Policy of The Regional Supervisory Board in Overcoming Business Competition Problems in The Determination of Honorarium By Notaries in The Kuningan District

The role of the Regional Supervisory Board (hereinafter referred to as Supervisory) in supervising Notary is very important, the goal is that Notary in carrying out their duties in their positions remain within the corridors of statutory regulations and the code of ethics. This study aims to determine the extent of the role of the Supervisory in supervising Notary in determining Honorarium outside the Rules of Notary Profession and under association provisions. This type of research is normative juridical. The method used in this research is literature study and interviews by interviewing several Notary and the chairman of the Regional Supervisory Board as respondents. The data obtained were analyzed using qualitative analysis techniques and then described. The results of the study show that the Regional Supervisory Board regarding its role in supervising Notary who determine the honorarium under the stipulations of the association and the Law on Notary Position can be summoned if there is a prior report from the public, however, the Supervisory should work and be active in terms of supervising Notary, because the Supervisory according to article 1 number 6 of the Rules of Notary Profession has given the authority to guide Notary.Keywords: Regional Supervisory Board; Notary; Role; Honorarium

Minimizing the sum of makespan on multi-agent single-machine scheduling with release dates

Competitive scheduling problems occur in integrated-services packet-switched networks, in which different applications compete for the same resource. Requests of each application arrive over time and contain multiple packets. This process can be described as a multi-agent single-machine scheduling (MSS) problem with release dates, where several packets (jobs) share a common network (processor) but are maintained by several competitive applications (agents) that optimize their criteria. The objective is to minimize the sum of makespans belonging to several agents individually. The NP-hardness of the model indicates that it cannot be optimally solved in polynomial time. For small-scale instances, an effective branch and bound (B&B) algorithm integrated with an elaborately designed pruning rule and a lower bound is developed to achieve exact solutions. Given the quality of service requirements and the periodical maintenance of networks, this problem is generalized to the weighted and periodic maintenance versions, respectively. For the weighted version, a hybrid discrete artificial bee colony (HDABC) algorithm integrated with effective improvement strategies is developed to achieve satisfactory solutions for medium-scale instances. For the periodic maintenance version, a deep reinforcement learning (DRL) method is introduced to obtain high-quality solutions in dynamic situation. Results of computational evaluation demonstrate the effectiveness of the proposed methods.

KORPORATIV BOSHQARUVNI SAMARALI AMALGA OSHIRISH

CURRENTLY, THE NECESSARY INSTITUTIONS OF A MARKET ECONOMY IN OUR COUNTRY ARE REFLECTED IN THE CURRENT LEGISLATION, AND THE MANAGEMENT EFFICIENCY IN NEWLY FORMED CORPORATE BUSINESS STRUCTURES IS LOW IN SOLVING THE PROBLEMS OF COMPETITION AND PROTECTION OF PROPERTY RIGHTS.

Reserve currency competition in a polycentric world financial system

This research is devoted to the issues of reserve currency competition in the global financial system. The paperaimsto investigate key sources of competitive advantages of reserve currencies in the context of the development of the global financial system towards currency multipolarity and assess how digital transformation can affect the drivers of reserve currencies’ competitive positions in the global financial system. The author uses the followingmethodsof scientific research: analysis, synthesis, abstraction, deduction, induction, and logical method. The article notes that the financial market capacity is the key factor of reserve currency competitiveness. The author emphasizes that monetary policy instruments that provide funding for financial institutions play a key role in strengthening reserve currency competitiveness in the global financial market. The author highlights that during the COVID-19 crisis monetary policy of the central banks that issue reserve currencies stabilized the situation in the world financial system and strengthened the positions of the major reserve currencies in the global financial market. The author notes that the increase of monetary policy cooperation between central banks points to the evolution of the world financial system towards currency multipolarity. The research emphasized that the development of ecosystems driven by digital transformation can significantly affect the competitive positions of currencies in the global financial system. The authorconcludesthat the global financial system is evolving towards currency multipolarity meaning that the US dollar will remain a leading reserve currency and at the same time other reserve currencies will likely play a bigger role.Further researchof currency competition problems may investigate the impact of digital transformation on competitive positions of reserve currencies in the global financial system.

White Shark Optimizer: A novel bio-inspired meta-heuristic algorithm for global optimization problems

This paper presents a novel meta-heuristic algorithm so-called White Shark Optimizer (WSO) to solve optimization problems over a continuous search space. The core ideas and underpinnings of WSO are inspired by the behaviors of great white sharks, including their exceptional senses of hearing and smell while navigating and foraging. These aspects of behavior are mathematically modeled to accommodate a sufficiently adequate balance between exploration and exploitation of WSO and to assist search agents to explore and exploit each potential area of the search space in order to achieve optimization. The search agents of WSO randomly update their position in connection with best-so-far solutions, to eventually arrive at the optimal outcome. The performance of WSO was comprehensively benchmarked on a set of 29 test functions from the CEC-2017 test suite for several dimensions. WSO was further applied to solve the benchmark problems of the CEC-2011 evolutionary algorithm competition to prove its reliability and applicability to real-world problems. A thorough analysis of computational and convergence results was presented to shed light on the efficacy and stability levels of WSO. The performance score of WSO in terms of several statistical methods was compared with 9 well-established meta-heuristics based on the solutions generated. Friedman’s and Holm’s tests of the results showed that WSO revealed reasonable solutions, in terms of global optimality, avoidance of local minima and solution quality, compared to other existing meta-heuristics.

Multi-Agent Reinforcement Learning for Joint Cooperative Spectrum Sensing and Channel Access in Cognitive UAV Networks.

This paper studies the problem of distributed spectrum/channel access for cognitive radio-enabled unmanned aerial vehicles (CUAVs) that overlay upon primary channels. Under the framework of cooperative spectrum sensing and opportunistic transmission, a one-shot optimization problem for channel allocation, aiming to maximize the expected cumulative weighted reward of multiple CUAVs, is formulated. To handle the uncertainty due to the lack of prior knowledge about the primary user activities as well as the lack of the channel-access coordinator, the original problem is cast into a competition and cooperation hybrid multi-agent reinforcement learning (CCH-MARL) problem in the framework of Markov game (MG). Then, a value-iteration-based RL algorithm, which features upper confidence bound-Hoeffding (UCB-H) strategy searching, is proposed by treating each CUAV as an independent learner (IL). To address the curse of dimensionality, the UCB-H strategy is further extended with a double deep Q-network (DDQN). Numerical simulations show that the proposed algorithms are able to efficiently converge to stable strategies, and significantly improve the network performance when compared with the benchmark algorithms such as the vanilla Q-learning and DDQN algorithms.

The Influence of Tecnology Adaptation and Market Orientation on Business Performance of BPR in Karanganyar with Competitive Advantage as the Mediation

The study addresses competition problems experienced by BPRs in Kabupaten Karanganyar. The competition from other financial instutions in particularly fintech has led the BPRs to experience a decline in particularly credit performance. The purpose of this study was to analyze the effect of new technology adaptation and market orientation on competitive advantage and business performance of BPRs in Kabupaten Karanganyar. The study selected executive officers and directors of 12 BPRs available in Kabupaten Karanganyar using purposive sampling. Those have worked for at least 3 years for the BPR were selected as the respondents and this resulted in 54 respondents. Data was collected using questionnaire and was analyzed using Structural Equation Modeling-PLS. The analysis indicates that new technology adaptation and market orientation have positive and significant effect on competitive advantage. New technology adaptation has direct effect on business performance, but market orientation shows indirect effect on business performance through competitive advantage. Competitive advantage is only proven to mediate the effect of market orientation on business performance and unable to mediate the effect of adaptation new technology on business performance.

Analysis of the dynamics of development and competitiveness of the Chinese gas industry

The object of research of this article is the natural gas industry of China, special attention is paid to competitive strength. Michael Porter's models cover many issues of the competition problem. The authors use M. Porter's five competitive forces to analyze China's gas industry. Together, these five factors influence the attractiveness of the industry and the decisions of competitive strategies in its place. Changes in various combinations of the five forces ultimately affect changes in the potential profit of the industry. The authors reveal the space of competitive forces, the competitive environment in the gas industry of the People's Republic of China, identified the driving and restraining forces of the gas industry of the People's Republic of China. The main conclusions of the study are: the main driving force in the gas industry in China comes from buyers, the restraining force in the gas industry in China mainly comes from the main competitors of the industry. China's economic development, demand for clean energy and increasingly advanced technologies for the development and use of natural gas are driving the development of China's gas industry. The raw materials of gas in China are highly dependent on imports, the construction of the infrastructure of the gas industry is difficult and expensive, and the efficiency of the use of the built gas industry is insufficient. Identification and analysis of the driving and binding forces of the industry, and the development of countermeasures are especially important to ensure the sustainable development of the industry.

Taming Digital Monopolies: A Comparative Account of the Evolution of Antitrust and Regulation in the European Union and the United States

This paper offers a comparative account of how the European Union and the United States surveil dominant internet players in light of recent enforcement efforts by U.S. antitrust agencies and ongoing discussions about regulating digital giants in both jurisdictions. After setting out themes for comparative analysis, the paper turns to the two actions initiated in the United States against Google: the one filed by the Department of Justice (DOJ) is similar in focus to the European Commission’s Android decision and the one led by the State of Texas focuses on advertising markets in a manner similar to the European Commission’s AdSense decision. We observe that while there are similar intuitions about anticompetitive conduct in the manner both jurisdictions address the issues, the framing of the competition problem by the U.S. agencies is more sophisticated in relation to the understanding of the markets, the theories of harm, and the design of forward-looking remedies. The paper then compares the Commission’s proposal for a Digital Markets Act with several Bills proposing platform regulation presently discussed in the United States, examining what the two systems have in common, what they may learn from each other, and what regulatory gaps remain.

How to improve the function of government carbon tax in promoting enterprise carbon emission reduction: from the perspective of three-stage dynamic game.

Flexible strategy of carbon tax is an important chip for the government to promote the implementation of carbon emission reduction. However, low-carbon technological innovation of enterprises is bound to produce market competition problems with traditional production technology. Based on this, in order to explore the relationship between heterogeneous objectives, carbon tax pricing strategy of government and decision-making of heterogeneous enterprise in the market, and how the government can make better use of carbon tax to promote the implementation of carbon emission reduction, this paper constructs and analyzes a three-stage dynamic game model between the government and heterogeneous enterprises. It is found that higher carbon tax pricing is not necessarily conducive to promote the implementation of carbon emission reduction. When the government's primary goal is to promote low-carbon technology innovative enterprise to increase innovative investment, the government should adopt the unified pricing strategy of carbon tax and improve carbon tax pricing; when the primary goal of the government is to promote the promotion of low-carbon products, the government should adopt the differentiated pricing strategy of carbon tax and reduce the carbon tax pricing of low-carbon technology innovative enterprise. In addition, this paper also studies the impact mechanism of different government pricing strategies on heterogeneous enterprise decision-making under heterogeneous objectives of government.

Public procurement and withdrawal as ways to meet public needs: problems of competition

Public procurement and withdrawal as ways to meet public needs: problems of competition

METHODOLOGY OF USING DEPTH-FIRST SEARCH (DFS) FOR SOLVING PROGRAMMING COMPETITION PROBLEMS

Depth First Search (DFS) is a well-known method for traversing a graph. In various situations, particularly in competition problems, the need for an effective application of DFS is masked by the conditions of the problem, or the data structures used. In these cases, the problem is either to identify the need to use DFS in the solution or to adapt the DFS to the particular conditions of the problem. This article is a study of representative competition problems, with the identification of DFS solutions, accompanied by IT solutions. The results will be useful to all those who are passionate about competitive programming, but also to those who study graph algorithms.

Problems of unfair competition in entrepreneurial activity

Problems of unfair competition in entrepreneurial activity

The Batum Subsystem of International Relations: Problems of Formation and Inter-Imperial Competition, June-August 1918

The implementation of the Treaty of Batum on 4 June 1918 signalled the hegemony of the Ottoman Empire in the macro-region between the Black and Caspian Seas. From the very first days it provoked opposition from other imperial actors, including Germany, an ally of Turkey. In June–July 1918, all the contenders for control of the post-imperial spaces of the former Ottoman Empire were forced to combine coercive and diplomatic means to strengthen their positions, recruiting allies and amassing forces. Due to a number of objective reasons, none of the great powers had the necessary resources to achieve their goals, facing a shortage of both military means and the necessary technical conditions. Their interest in the transformation of the region was extremely high: Germany and Soviet Russia sought to incorporate Transcaucasia into the space of the larger Brest system, while the Entente and the Central Powers were still engaged in a decisive campaign of the Great War, and the Young Turks saw their only chance of implementing their nationalist projects. The hostages of these aspirations were the newly emerged limitrophe states, which were in various stages of formation, on both sides of the Caucasus range. The German mission to Georgia, the Ottoman assistance to Azerbaijan and the Mountainous Republic, and Armenia's hopes for assistance from Britain, Soviet Russia or Austria-Hungary all played a decisive role in their fate. The policy of the great powers was complicated by problems of coalition interaction and systemic trends towards the formation of a coherent geopolitical space following the victory of the Central Powers over the disintegrating Russian Empire and Romania. The peace conference in Constantinople failed to resolve the problem, and the Entente's efforts to re-establish the Eastern Front in parts of the former Russian Empire were growing. Interaction and competition between various actors led to the active integration of the macro-region into the logic of the Great War, so that attempts to diplomatically formalise or revise the Batum subsystem were soon replaced by military confrontation between all the imperial claimants around Baku. The article draws on the diplomatic archives of the former Central Powers to reconstruct the formation of a new subsystem of international relations.

The influence of China's Unified Qualification Exam for Legal Professionals on China's legal education and its solution

Under the background of the formal establishment of China's Unified Qualification System for Legal Professionals, the long-standing problem of independence and competition between undergraduate legal education and qualification exam for legal professionals has become more prominent in China. In order to ensure the efficiency of legal education and the accurate identification of qualified legal talents in the qualification exam for legal professionals, we should re-understand the normal relationship between the undergraduate legal education and the qualification exam for legal professionals, connect the undergraduate legal education with the qualification exam for legal professionals, rationally view and actively solve the impact of the qualification exam for legal professionals on the study and employment of law school students .We should adjust the orientation of undergraduate legal education through policy promotion, and reform the qualification exam for legal professionals at the same time, so that the two can be better connected, so as to promote the development of legal education.

Pharmaceutical supply chain network and competitive distributor location

This paper proposes a bi-level, integer programming, and nonlinear model for the competitive location problems in the pharmaceutical supply chain. Existing and candidate distributors compete to successively service customers in competitive supply chain. It proposes a mathematical model for the Darou Pakhsh pharmaceutical supply chain where the upper level tries to propose the best locations for the distributors and the lower level selects the best distributors to cover the demand areas. The proposed mathematical model presents important factors such as the business share of the market and utility to optimise the competitive distributor location in the case study. Decision-makers are also interested in finding the rank list of distributors; therefore, the MADM method, VIKOR, is proposed to select the best distributors among different alternatives according to critical criteria. Finally, sensitivity analysis is used to analyse the effectiveness of the radius of influence of distributors' parameters on the follower objective function.

Improved Sparse Signal Recovery via Adaptive Correlated Noise Model

Sparse signal recovery consists of employing a sparsity promoting regularizer to estimate the underlying signal from an incomplete set of measurements. Typical recovery approaches involve an alternating procedure where the estimate of the signal is progressively refined through filtering its degraded observation by a denoiser. The filter acts, implicitly, as a regularizer for the estimate. Hence, the implicit regularization is determined by the signal model underlying the denoising filter, as well as by the model of effective noise (i.e. degradation to be filtered) adopted by the filter. We improve the recovery by an adaptive stationary correlated noise model and the corresponding denoiser in place of the traditional filters for uncorrelated white noise. The effective noise can vary as the recovery progresses and we track these variations by estimating the noise correlation at every iteration. Competitive inverse problems are considered as benchmarks, including compressive spectral/temporal imaging and 2D/3D tomography. Analysis of the effective noise within each application demonstrates that it features various forms of correlation, which if leveraged by a denoiser lead to a better and faster signal recovery.

Photonic decision making for solving competitive multi-armed bandit problem using semiconductor laser networks

Photonic decision making for solving competitive multi-armed bandit problem using semiconductor laser networks

A competitive facility location problem using distributor Stackelberg game approach in multiple three-level supply chains

This paper studies a discrete facility location problem in two different supply chains including suppliers, distributors and customers. The current and new distribution firm act as the leader and the follower respectively in a Stackelberg game. The model considers the lead-time as a competitive factor between the new Distribution Centres (DCs) and the existing ones as well as optimising the location and number of to-be-established DCs in the new supply chain by minimising the total cost. The Branch and Bound as well as Genetic Algorithm (GA) are used for solving the model, and the results are compared with the situation that there is no competitor results show in case of competition; there is more possibility of lost sales ignoring the rival decision in making strategic decision of locating new DCs. While, when there is no other player, decisions are taken independently as the only possible option for consumers.

An application of the quadrilateral's geometry in solving competitive planimetric problems

An application of the quadrilateral's geometry in solving competitive planimetric problems