内控失效与合规问题的防范与应对策略研究

建立健全企业的内部控制体系和合规问题的防范方法,对企业的可持续发展具有十分重要的现实意义。随着市场经济体系逐步发展健全,企业面临的市场竞争关系越来越激烈,这就要求企业要在企业内部进行有效的管理,提升员工的素质,为企业创造更好的发展前景。但是,由于内控体系的不健全,合规意识不强,缺乏有效的监管机构和信息化建设不完善等问题,造成企业长久以来发展缓慢。因此本文从健全内控体系和合规问题防范的意义出发,分析了内控实效与合规存在的问题,并提出了相关应对策略。

出海企业的合规问题及其应对策略

近年来,我国企业遭受海外处罚的事件频发,合规问题正成为出海企业普遍面临的一个重要问题。出海企业的特殊性使其合规运营的难度较大,运营过程中产生的合规问题也更加多样化,违规行为的负面影响不可估量。本文以出海企业为研究对象,通过典型案例,对出海企业合规运营的难点、合规问题的分类进行分析,探讨了合规问题的风险及其应对策略。

电子商务时代下审计信息化的合规问题分析

文章旨在探讨电子商务时代下审计信息化的合规问题。随着信息技术的快速发展,电子商务已经成为现代商业活动的主要形式。在这一背景下,审计也面临着从传统方式向信息化方式的转变,这引发了一系列合规性问题。文章首先分析了电子商务与审计的影响,接着从数据隐私、网络安全等几个方面探讨了电子商务审计信息化过程中的合规性挑战。通过深入剖析,可以更好地理解并应对电子商务时代下审计信息化所面临的合规性问题。

临床研究中医疗保险基金合规问题分析及管理对策

目的临床研究在医疗机构内广泛开展,试验研究和常规医疗经费使用有差别,本文旨在分析试验研究中医疗保险基金合规问题,探索试验机构内的管理策略。方法通过查阅文献,问卷及工作实践,分析国内临床试验研究中医疗保险基金合规问题的现状和存在问题,提出有针对性的经费使用的管理措施,规范相应的工作流程。结果本文总结出3种试验相关经费的支付方式,分析目前存在的主要问题为试验要求检查的界定、方案规定的联用药物的支付、医疗器械试验的特殊性、试验中不良事件费用支付、上市后研究以及临床试验的保险。根据法规要求和工作实践,梳理出相应的管理对策,开展试验机构内部应进行项目经费和保险审核,试验研究、医疗保险管理部门、伦理委员会等分工协作共同建立完善合规管理体系,研究团队加强不良事件管理,加强受试者的宣教,利用好共享平台。结论试验研究机构建立规范可行的各项流程,研究团队强化实施管理,利用共享平台有利于确保医疗保险基金合规使用,保护受试者利益。

医院采购合同管理的合规风险识别与策略研究

医院采购合同管理是医疗机构运行的重要环节,其合规性问题严重影响医院的合法权益和运营效率。本文首先对医院采购合同管理的背景与意义进行深入阐述,明确其在医院运营管理中的关键作用;并通过对合规性问题的定义和特性分析,明确不规范的合同管理行为对医院采购效率和经济利益产生的负面影响。针对此类问题,本文提出了加强内部合规管理、完善合同管理体系、以及加强外部合规合同监管等解决策略,以期通过完善医院采购合同管理,提高医院的运营效率和经济效益。最后,本文通过综述和展望,对未来医院采购合同管理合规性问题的研究提出了建设性意见,为善待医院采购合同管理中的合规性问题,提供了一种具有参考意义的解决方向。

新三板上市中财务合规性问题的研究

在我国中小企业经营发展过程中,新三板上市中财务合规是重点考虑问题,关系到企业的未来发展。为保证财务合规性问题不会影响企业挂牌,应该对此问题深层次分析,诸如内部控制问题、持续经营能力问题、财务管理基础问题等。同时对问题成因深入剖析,在遵循合法性、适应性、效用性原则的基础上,企业合理制定应对办法,保证问题在有效解决的同时,保持可持续发展进程的有序推进。

刍议商业银行合规风险管理

合规风险是指商业银行因没有遵循合规法律、规则和准则而可能遭受法律制裁、监管处罚、重大财务损失和声誉损失的风险。有效的合规风险管理是商业银行构建全面风险管理体系的基础,因此,加强合规风险管理显得十分重要。文章从界定商业银行合规、合规风险以及合规风险管理等概念出发,指出了当前商业银行合规风险管理方面存在的主要问题,明确了加强商业银行合规风险管理需遵循的几项制度,进而提出了相应的具体实施路径。

财务记账中原始凭证的合规性问题及其对策探讨

原始凭证是否合规,直接关系企业财务管理的效率与水平,在实际工作中,原始凭证容易出现不合规问题。为此,本文从财务记账的角度,对原始凭证的合规性问题进行了归纳和总结,并结合笔者多年的工作实践,提出了相关的对策建议,以期为提高企业财务管理水平提供有益参考和借鉴。

Hybrid particle swarm optimization with chaotic search for solving integer and mixed integer programming problems

A novel chaotic search method is proposed,and a hybrid algorithm combining particle swarm optimization(PSO) with this new method,called CLSPSO,is put forward to solve 14 integer and mixed integer programming problems.The performances of CLSPSO are compared with those of other five hybrid algorithms combining PSO with chaotic search methods.Experimental results indicate that in terms of robustness and final convergence speed,CLSPSO is better than other five algorithms in solving many of these problems.Furthermore,CLSPSO exhibits good performance in solving two high-dimensional problems,and it finds better solutions than the known ones.A performance index(PI) is introduced to fairly compare the above six algorithms,and the obtained values of(PI) in three cases demonstrate that CLSPSO is superior to all the other five algorithms under the same conditions.

Multi-objective Evolutionary Algorithms for MILP and MINLP in Process Synthesis

Steady-state non-dominated sorting genetic algorithm (SNSGA), a new form of multi-objective genetic algorithm, is implemented by combining the steady-state idea in steady-state genetic algorithms (SSGA) and the fitness assignment strategy of non-dominated sorting genetic algorithm (NSGA). The fitness assignment strategy is improved and a new self-adjustment scheme of is proposed. This algorithm is proved to be very efficient both computationally and in terms of the quality of the Pareto fronts produced with five test problems including GA difficult problem and GA deceptive one. Finally, SNSGA is introduced to solve multi-objective mixed integer linear programming (MILP) and mixed integer non-linear programming (MINLP) problems in process synthesis.

Multi-objective modeling and optimization for scheduling of cracking furnace systems

Cracking furnace is the core device for ethylene production. In practice, multiple ethylene furnaces are usually run in parallel. The scheduling of the entire cracking furnace system has great significance when multiple feeds are simultaneously processed in multiple cracking furnaces with the changing of operating cost and yield of product. In this paper, given the requirements of both profit and energy saving in actual production process, a multi-objective optimization model contains two objectives, maximizing the average benefits and minimizing the average coking amount was proposed. The model can be abstracted as a multi-objective mixed integer non- linear programming problem. Considering the mixed integer decision variables of this multi-objective problem, an improved hybrid encoding non-dominated sorting genetic algorithm with mixed discrete variables （MDNSGA-II） is used to solve the Pareto optimal front of this model, the algorithm adopted crossover and muta- tion strategy with multi-operators, which overcomes the deficiency that normal genetic algorithm cannot handle the optimization problem with mixed variables. Finally, using an ethylene plant with multiple cracking furnaces as an example to illustrate the effectiveness of the scheduling results by comparing the optimization results of multi-objective and single objective model.

Optimization of Portfolio of Stocks at ZSE through the Analysis of Historical Data

Decision-making of investors at the stock exchange can be based on the fundamental indicators of stocks, on the technical indicators, or can exist as a combination of these two methods. The paper gives emphasis to the domain of technical analysis. In the broader sense the technical analysis enables the dynamics of the expected future values of the shares estimation. This can be performed on the basis of the data on historical trends of the revenues, profits and other indicators from the balance sheet, but also on the basis of historical data on changes in the values of the shares. Companies generally belong to the different sectors that have different presumptions of development resulting from the global market trends, technology and other characteristic. Processing of historical data values of the outstanding shares of the Zagreb Stock Exchange （ZSE） is origination of this research. Investors are interested to know the estimation of future returns for the stocks as well as the size of the risk associated with the expected returns. Research task in this paper is finding the optimal portfolio at the ZSE based on the concept of dominant portfolio by Markowitz approach. The portfolio is created by solving non-linear programming problem using the common software tools. The results of obtained optimal portfolios contain relevant conclusions about the specifics of the shares as well as the characteristics of the industrial sectors but also provide a further knowledge about diverse sectors treatment at the stock exchange in a multi-year period.

Legal and Economic Aspects of the Operation of Cooperatives in Polish Agriculture

The article presents the legal and economic issues connected with the formation and operation of Polish agricultural cooperatives. Additionally, it shows a brief history of cooperative development on Polish lands and statistical data on agriculture and cooperatives. Most attention is given to dairy cooperatives, cooperative groups of agricultural producers and agricultural production cooperatives. These types of cooperatives are the most popular in Polish agriculture. The fundamental law regulating the issue of cooperatives in Poland is the Cooperative Law Act of September 16, 1982. Other laws, however, also have a big influence on the business activity of agricultural cooperatives, especially the EU legal regulations. Poland membership in the European Union has created new possibilities of development for the cooperative movement.

Modeling and optimization methods of integrated production planning for steel plate mill with flexible customization

With diversified requirements and varying manufacturing environments, the optimal production planning for a steel mill becomes more flexible and complicated. The flexibility provides operators with auxiliary requirements through an implementable integrated production planning. In this paper, a mixed-integer nonlinear programming(MINLP) model is proposed for the optimal planning that incorporates various manufacturing constraints and flexibility in a steel plate mill. Furthermore, two solution strategies are developed to overcome the weakness in solving the MINLP problem directly. The first one is to transform the original MINLP formulation to an approximate mixed integer linear programming using a classic linearization method. The second one is to decompose the original model using a branch-and-bound based iterative method. Computational experiments on various instances are presented in terms of the effectiveness and applicability. The result shows that the second method performs better in computational efforts and solution accuracy.

Multi-Objective Cooperative Salvo Attack Against Group Target

This paper proposes a solution for the problem of cooperative salvo attack of multiple cruise missiles against targets in a group. Synchronization of the arrival time of missiles to hit their common target, minimizing the time consumption of attack and maximizing the expected damage to group targets are taken into consideration simultaneously. These operational objectives result in a hierarchical mixed-variable optimization problem which includes two types of subproblems, namely the multi-objective missile-target assignment（MOMTA） problem at the upper level and the time-optimal coordinated path planning（TOCPP） problems at the lower level. In order to solve the challenging problem, a recently proposed coordinated path planning method is employed to solve the TOCPP problems to achieve the soonest salvo attack against each target. With the aim of finding a more competent solver for MOMTA, three state-of-the-art multi-objective optimization methods（MOMs）,namely NSGA-II, MOEA/D and DMOEA-εC, are adopted. Finally, a typical example is used to demonstrate the advantage of the proposed method. A simple rule-based method is also employed for comparison. Comparative results show that DMOEA-εC is the best choice among the three MOMs for solving the MOMTA problem. The combination of DMOEA-εC for MOMTA and the coordinated path planning method for TOCPP can generate obviously better salvo attack schemes than the rule-based method.

BILEVEL PROGRAMMING MODEL AND SOLUTION METHOD FOR MIXED TRANSPORTATION NETWORK DESIGN PROBLEM

By handling the travel cost function artfully, the authors formulate the transportation mixed network design problem （MNDP） as a mixed-integer, nonlinear bilevel programming problem, in which the lower-level problem, comparing with that of conventional bilevel DNDP models, is not a side constrained user equilibrium assignment problem, but a standard user equilibrium assignment problem. Then, the bilevel programming model for MNDP is reformulated as a continuous version of bilevel programming problem by the continuation method. By virtue of the optimal-value function, the lower-level assignment problem can be expressed as a nonlinear equality constraint. Therefore, the bilevel programming model for MNDP can be transformed into an equivalent single-level optimization problem. By exploring the inherent nature of the MNDP, the optimal-value function for the lower- level equilibrium assignment problem is proved to be continuously differentiable and its functional value and gradient can be obtained efficiently. Thus, a continuously differentiable but still nonconvex optimization formulation of the MNDP is created, and then a locally convergent algorithm is proposed by applying penalty function method. The inner loop of solving the subproblem is mainly to implement an Ml-or-nothing assignment. Finally, a small-scale transportation network and a large-scale network are presented to verify the proposed model and algorithm.