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Joint Replenishment Problem under Fuzzy Environment

On 31/10/2014, in Economics papers, by rain

The Joint Replenishment Problem refers to jointly ordering various items from the same supplier to replenish inventory with the privileges of reducing the annual ordering times, obtaining discounts, saving expenses of inventory control as well as lowering the cost of items. When a group of goods are supplied by the same supplier (or from the same supply place), or when a group of goods are transported by vehicles, we are confronted with the problem of how to reasonably coordinate and arrange orders to minimize the cost. In the former researches, the issue of joint replenishment problem has been conducted considering certainty demand rate or certainty costs problems. However in practice, many factors are nondeterministic from the uncertainty environment of Joint Replenishment Problem, thus these uncertain factors should be considered in Joint Replenishment Problem.Firstly, the Joint Replenishment Problem with fuzzy demand was studied. Use the trapeziform fuzzy number to represent the fuzzy demand and fuzzy programming model was constructed. A Genetic Algorithm (GA) was presented to solve the JRP model with fuzzy programming model and discussed the genetic operations. Numerical examples and program flow chart were given to illustrate the theory of the problem.Secondly, the Joint Replenishment Problem with fuzzy major ordering cost and fuzzy resource constraint was studied. The fuzzy variable is represented with triangular fuzzy number. Fuzzy programming model was constructed with fuzzy expected definition and possibility theory. Two methods which Combing GA and fuzzy simulation and converting the fuzzy model into the crisp model are used to solve the fuzzy programming model. Finally a numerical example is provided.Finally, the algorithm and model have been applied in the inventory Management system to verify the feasibility of the algorithm.

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Two Models of Portfolio Selection under Fuzzy Condition

On 14/08/2012, in Management, by rain

【Abstract】 The study of Investment and financing decision-making in captial market attract everyone’s attention after the naissance of portfolio Investment theory and take a rapid development.Using mathematics, Harry M.Markowitz, the Economics Nobel Laureate in 1990, expressed strictly the saying ” don’t put eggs in one basket ” with scientific words, upbuilt the conception and theory of portfolio optional, and found operable method in Computer, so, the foundation of portfolio selection was founded. William Sharpe brought Markowitz’s theory forward and advanced Capital Asset Pricing Model (CAPM). Purtherly, using coefficient β to measure system risk of the firm, he established connection between negotiable securities expected return rates and its β coefficient, laid a foundation of investment, upgraded the study of portfolio selection to a new highness, as a result, CAPM become a important analysis method of finance risk investment.Miller and Modigliani set up a theory about financing decision-making MM theory to research finance leverage and corporation merit and to guide corporation makeing decision about financing.In fact we can’t describe accurately the character of captial firmly because of many dubious factors in negotiable securities market. So we give a estimate for captial expectation yield and use fuzzy number to describe its expected return rates, which make the model more significant.In this paper we focus on two fuzzy-linear program models of portfolio investment in which expected return rates is fuzzy numbers.Firstly, using thesatisfaction of constraints of symmetry triangle fuzzy number and assuming the risk is not bigger than a given number,we selecte a investment proportion to make return rate maximal. Secondly, we discuss, when return rates is a given number, how to make decision on restriction borrowing rate with superior assets for firms to make risk minimal. Furthermore, when borrowing rates vary, how to change its investment proportion.

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Comprehensive Appraisal Method and Case Study about the Selection of Power Plant Location

On 22/06/2012, in Agriculture, by rain

【Abstract】 When a power plant is built, site selection is the precondition of the plant to develop. It can both impact the time limit and the cost for a project and the rationality, the reliability and economy to operate, so rational site selection is important to the development of the plant in the future. In the thesis, after the enough data is referred and the factor is considered fully to site selection, the index system is established and analytic hierarchy process is used to establish the weight. Fuzzy synthetic appraisal model and fuzzy programming model are used to compare the pending scheme so that the supreme one can be selected. The thesis is orientating to the practical academic application. Through the methods has been utilized, the three choosed sites of some plant in some area are valued. The result got is according to the one that is choosed by the Enterprise finally and can prove that the methods researched in the thesis is applicable to choose the site of plant.

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Research on Stackelberg Game of a Supply Chain with Uncertain Demand of Perishable Goods

On 28/02/2012, in Management, by rain

【Abstract】 Perishable goods was characterized by short sales period,low salvage,demand uncertainty etc.Since new generations are launched quickly,the information of probability distribution of the perishable goods market demand cannot be gotten due to lack of historical data.It is reasonable to give a subjective assessment by expert to the market demand.This paper characterizes the market demand of perishable goods as a fuzzy variables put forward by uncertainty theory,and make research on Stackelberg game of a supply chain with uncertain demand.Firstly,consider a supplier-dominant supply chain with one supplier and multi-retailers,a fuzzy bilevel expected value model and a fuzzy chanceconstrained model are fbrmulated for this kind of problem.To solve the problem, by simulating the decision process a hybrid algorithm based on particle swarm optimizer(PSO),neural network and fuzzy simulation is developed and numerical examples are provided to illustrate the effectiveness of the algorithm.Secondly, consider a retailer-dominant supply chain with one supplier and one retailer,a fuzzy bilevel expected value model is formulated.we define the fuzzy expected Stackelberg equilibrium strategy,and prove the existence of the equilibrium.

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Optimization Model of Maintenance Planning and Auto-Evaluation Process to MRO Enterprise

On 27/01/2012, in Agriculture, by rain

【Abstract】 The dissertation concerns with models and algorithms for various fuzzy aggregate maintenance planning . The major works are given as follows:(1) First, presents a systematic methodology to construct a reliability prediction model for aircraft reliability based on spare parts invalidation data. SOM is used to combine the analytic the scatter spare parts invalidation data into a sequence model based on the time-to-failure data extracted from the repair registers. Its effectiveness is illustrated by Mean Time Between Failures (MTBF) study and analysis of real invalidation data. The proposed method can help proactively diagnose spare parts faults with a sufficient lead time before actual system failures to allow preventive maintenance to be scheduled thereby reducing the downtime costs.(2)Secondly, a hierarchy model is established about the evaluation of servicing process. When the model is analyzed by analytical hierarchy process (AHP), the weighted coefficients influencing the evaluation and selection process are obtained, and the evaluation matrix is establish by data envelopment analysis (DEA). The hierarchy structure model is implemented based on .NET, the simulation credibility of this method is proved validity.(3)Then, considered strong seasonal characteristics of the aviation maintenance market, aircraft maintenance planning model with fuzzy demand and production capacity constraints was proposed through analyzing the aircraft maintenance process for the airline, spare parts requirement and airline flights planning. Under the background of aircraft maintenance enterprises, the model and algorithm on maintenance planning for the decision-making system in uncertainty environment were put forward. Based on theories of fuzzy math and probability , maintenance planning and control model was designed to establish a reconfigurable optimized maintenance planning.(4) A solution based on .NET Framework and Web Services technology is presented,which illuminates how to construct the spare parts order and repair system for the exigent requirements of airline company after the analysis and discussion of business requirements and .NET Architecture. By the full use of Service-Oriented Architecture(SOA) and Role-based Control(RBAC),the solution makes the supply chain more fluent inside the airline company.

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Research and Application of Inventory Control Policy under Fuzzy Environment

On 24/01/2012, in Management, by rain

【Abstract】 Inventory Management models are used widely in practical world and they can help the decision-makers to obtain the optimal production or ordering lot sizing effectively. For the traditional inventory Management models, researchers always assume the key parameters involved in inventory management system such as costs and demands are all constant values, then make decision to obtain the production or ordering lot sizing of single-item or multi-items. But in fact, many factors are nondeterministic. For example, the demand fluctuates as the market changing and cost is affected by the season change, which form the uncertainty environment of inventory management system. These uncertain factors should be considered in inventory planning control system.Firstly, two single-item inventory management models are considered. One is researched as the demand is continuous fuzzy number without considering Deterioration. A model is established to minimize the cost and solved by the method of integral sorting to obtain the optimal ordering lot sizing, then a numerical example is provided to illustrate the problem. The other is the inventory management model on deteriorating item that the demand is nondeterministic and a model is established to maximize the average net profit. The fuzzy parameters fluctuation range is estimated by the method of confidence intervals, then the model is defuzzied by the method of signed distance and optimized to receive the production quantity satisfying the constraints. Finally a numerical example is also provided to illustrate the problem.Secondly, the inventory management model of multi-items with fuzzy costs and inventory capacity restriction is considered. An expected value model is established based on fuzzy costs and fuzzy constraints. For seeking the solution of uncertain model, this dissertation discusses the theory of fuzzy programming and designs a hybrid intelligent algorithm based on fuzzy simulation, neural network, genetic algorithm, and the genetic operation, such as coding, mutation, selection and crossover etc. Lastly the feasibility and validity of this model and algorithm is illustrated by using simulation data and hybrid intelligent algorithm.Finally, the development of a inventory prototype system is introduced, in which the results of the research are applied. The feasibility and application value of fuzzy inventory model is displayed fully.

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Research on the Theories and Methods about Transportation Corridor and Path Analysis

On 14/01/2012, in Management, by rain

【Abstract】 Transportation corridor, also named transportation thoroughfare or traffic passageway, is the inevitable result produced when the traffic and transportation industry comes into the age of integrated transportation. Some theories and methods related to transportation corridor are studied in this paper, and an analysis and evaluation on transportation hub, transportation mode and transportation network of road and so on, is also made. The main contents include:(a) The definition, signification and characteristics of transportation corridor are concluded. The structure and classification of corridor are also expounds. Moreover, an analysis on the characteristics of transportation corridor is also made, based on which, the analysis and evaluation content system is put forward combined with three research scales of transportation.(b) According to the characteristics of integrated hub, an evaluation index system for the importance of integrated transportation hub is constructed. Then, with the method of Analytic Hierarchy Process (AHP), the hub is evaluated, and an experiment is carried out.(c) A transportation route selection model is built with the method of Ambiguity Optimization; a model of transportation mode selection inside the corridor is built with AHP and an experiment is carried out.(d) With the technology of fuzzy compromise programming, an optimal route model with multi-object of the road network is constructed, and the realization algorithm as well as the correlative sample is offered. Then, combined the research, an optimal route analysis experiment based on MapObjects is designed and implemented.The research in this paper is quite significant both academically and practically, for it not only provides theories and methods for the analysis and evaluation on transportation corridor, but also offers a scientific reference to carry out similar researches.

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Returns Policy Model for Supply Chain with E-marketplace in Fuzzy Environment

On 05/01/2012, in Management, by rain

【Abstract】 With the development of the network technology and electronic commerce, more and more people started on-line shopping. E-market gradually becomes a key factor for a company especially because of the Internet global openness, product selling poorly in a little area may still have certain need especially on a global scale. In this case, integrates the electronic market to the supply chain Management, the company can win in the competition.On the other hand, the information of a probability distribution of the goods market demand can not be gotten due to lack of historical data. It is reasonable to give a subjective assessment by expert to the market demand.This thesis gives a system framework and model of returns policy for supply chain with e-marketplace in fuzzy environment. This paper characterizes the traditional and e-market demand of goods as fuzzy variables put forward by uncertainty theory. A fuzzy expected value model is formulated for this problem. To solve the problem, by simulating the decision process a hybrid algorithm based on particle swarm optimizer (PSO), neural network and fuzzy simulations is developed and numerical example is provided to illustrate the effectiveness of the algorithm.

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Research on Locating Unwanted Logistic Facilities

On 02/01/2012, in Management, by rain

【Abstract】 Location problems are mainly focused on how to locate facilities in a programming area as to optimize the problem objectives and further to provide decision makers with best locating solutions. This sort of problems appears in various fields of Social life and production activities, and they are important decision problems which bear long-term benefits. Moreover, with the speed up of globalization, and the wide spread of the belief of sustainable development and environment awareness, the location problems of unwanted facilities, particularly, landfills, have earned growingly concern around the world. And at present in China, much of the trash is dumped.To help solve the problem in the framework of environment and economy, this paper develops a multi-objective model for determining locations of landfills, typical unwanted facilities. The first section is a review on the historical development of location problems as well as the state of art. In the second part, a brief introduction of the prerequisite knowledge on fuzzy mathematics is supplied. Next, a multi-objective model for locating landfills is proposed; also its solution properties are discussed in detail. And the fourth section is an extension of the former part, which gives an introduction to the present research on recycling logistics. The last chapter is about further research directions.Our main work are as follows: (1)The model objectives considered are minimization of the total cost and the total measure of risk and the equitable distribution of risk among the population centers; (2)As to the general multi-objective model dealt with fuzzy goal programming, discussions are detailed whether its fuzzy optimal solutions are inner-related with weak efficient solutions and efficient ones as well; (3)And to demonstrate the applicability of the model, a numerical example is provided using two different solution approaches. The results indicate that the weight additive goal programming can help to generate satisfactory solutions at a more acceptable achievement level; (4) Also, we propose a multi-objective logistic facility location model, which takes into consideration the types of waste and the different disposal techniques.

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Modeling and Solving for Production Scheduling Optimization of a Refinery Plant

On 06/12/2011, in Management, by rain

【Abstract】 Production scheduling is important for the refineries because it concerns many sections such as inventory, supply chain, blending, equipment processing etc. In order to gain the maximum profits, it is necessary to make a good scheduling. This thesis presents four production scheduling models for a refinery by using mathematical programming, and different solving algorithms respectively. The main works of this thesis are as follows:A production scheduling model of a single goal linear programming for a refinery plant is presented. There are five processing units in the refinery plant which includes two atmospheric vacuum distillation units, a catalytic cracker, a solvent oil equipment and a gas separation unit. The objective function of the optimization is to maximize the profit of the refinery in a period and the constraints are mass balance, equipment processing capacity quality demand, tank capacity, energy consumption constraint and inventory constraint.Because of the nonlinearity of gasoline octane number in oil blending, a model of single goal nonlinear programming is addressed according to the quadratic nonlinearity oil blending model by Twu-Coon method. A hybrid genetic algorithm (GA), which makes use of the position displacement strategy of the particle swarm optimizer (PSO) as a mutation operation, is applied to solve the nonlinear programming model. The model is validated by the result researched.Considering the uncertain price in the oil market, a production scheduling model of fuzzy linear programming is presented based on the theory of fuzzy programming. The fuzzy programming is transformed into a deterministic multi-objective programming by taking three typical numbers which are minimum values, most probable values and maximum values within the price range instead of the fuzzy number, and then solved by using minimax algorithm. On account of the time-varying factors, a dynamic programming model with multistage production scheduling is addressed with the profits as objective function and mass balance, equipment processing capacity quality demand, tank capacity, energy consumption and inventory as constraints. The decision variables are the production of the refinery product in multistage and the state variables are inventory. Because of the inequality constraints, ordinary method for solving dynamic programming is unsuitable. In this thesis, the total income expression is expanded into the sum of profits in each period, and then the dynamic programming is transformed into nonlinear programming with inequality constraints which is solved by using hybrid genetic algorithm. At last, a calculating example is given to verify the validity of the model.