Abstract:
This study presents a cost optimization model for multi-item inventory system having deterministic demansd. We assume that backlogging is allowed. The maximum capacity of the inventory is assumed to be constant Qi. The total annual variable cost is derived in terms of Qi and it is a non-linear function of Qi. First the deterministic inventory problem is solved using constrained optimization technique. In addition to the above, we assume that the total expenditure and floor space are not precisely measured function. A non-linear programming problem is formulated and solved by Lagrange multiplier method. Numerical examples are provided for deterministic inventory problem to emphasize the results in crisp.

Abstract:
In this paper, a multi-item inventory model with space constraint is developed in both crisp and fuzzy environment. A profit maximization inventory model is proposed here to determine the optimal values of demands and order levels of a product. Selling price and unit price are assumed to be demand-dependent and holding and set-up costs sock dependent. Total profit and warehouse space are considered to be vague and imprecise. The impreciseness in the above objective and constraint goals has been expressed by fuzzy linear membership functions. The problem is then solved using modified geometric programming method. Sensitivity analysis is also presented here.

Abstract:
Item Response Theory (IRT) is a popular assessment method used in education measurement, which builds on an assumption of a probability framework connecting students' innate ability and their actual performances on test items. The model transforms students' raw test scores through a nonlinear regression process into a scaled proficiency rating, which can be used to compare results obtained with different test questions. IRT also provides a theoretical approach to address ceiling effect and guessing. We applied IRT to analyze the Force Concept Inventory (FCI). The data was collected from 2802 students taking intro level mechanics courses at The Ohio State University. The data was analyzed with a 3-parameter item response model for multiple choice questions. We describe the procedures of the analysis and discuss the results and the interpretations. The analysis outcomes are compiled to provide a detailed IRT measurement metric of the FCI, which can be easily referenced and used by teachers and researchers for a range of assessment applications.

Abstract:
Background: No indigenous screening instruments are available for the detection of depression and suicide risk relevant to the context of patients in Uganda. The Response Inventory for Stressful Life Events (RISLE) may be an appropriate tool, but requires validation. Objective: The paper reports on the development of the RISLE and the refinement of the 100-item RISLE into a shorter version for use in large samples. Methods: Two samples were used in the validation exercise: a general population sample from Adjumani and Bugiri districts and a student sample from Makerere University in Kampala district. The RISLE responses were subjected to Principal Components Analysis and Discriminant Function Analysis. The 100-item RISLE and resulting shorter version were compared and their concurrent validity assessed by comparing test results to the individuals' responses to the Beck Depression Inventory (BDI) and the Beck Scale for Suicide ideation (BSS). Results: Nine hundred thirty nine questionnaires were available for the population sample, 101 for the student sample. The 100item RISLE was reduced to 36-items without loss of face validity. Both the 100- and 36-item versions had high internal consistency, were highly correlated with each other and with the BDI and BSS. Conclusion: The 36-item RISLE appears to be an advance on the 100-item version, retaining its internal consistency and concurrent validity. African Health Sciences Vol.5(2) 2005: 137-144

Abstract:
The present study extends the Huang`s model by considering decay item under two levels of trade credit. At first, we model the retailer`s inventory system as a cost minimization problem. Then, we prove the convexity of the retailer`s inventory system developed in this study. Finally, a theorem is developed to determine the retailer`s optimal replenishment cycle time efficiently.

Abstract:
提出了一种考虑维修比例的民机备件多级库存配置方法，将维修比例引入METRIC（multi-echelon technique for recoverable item control）模型建立多级库存配置模型，运用边际分析法对模型进行求解进而实现备件多级库存配置。首先，阐述了考虑维修比例的多级库存配置模型的原理，建立了以机队可用度为优化目标、费用和保障率为约束数学模型；然后，论述了基于边际分析法的考虑维修比例影响的情况下多级库存配置模型求解流程；最后，以典型民机起落架航线可更换单元（line repairable units，LRU）为研究对象，在考虑维修比例影响的情况下对其多级库存配置进行研究。算例分析结果表明：在满足优化约束条件的情况下，最小的保障费用为2 759 833美元，机队可用度为0.980 6，并得到此时LRU多级库存配置数量；通过方法比较验证了考虑维修比例的维修资源多级库存配置模型的可行性和有效性。在合理降低成本的前提下，为精确地配置维修资源多级库存优化提供指导。 A multi-echelon inventory allocation technique with maintenance ratio for civil aircraft spare parts was proposed in this paper. Multi-echelon inventory allocation model was established, which integrates maintenance rate into METRIC (Multi-echelon technique for recoverable item control) model, and then marginal analysis method was applied to solve this model and accomplish multi-echelon inventory allocation of spare parts. Firstly, the theory of multi-echelon inventory allocation model with maintenance ratio was elaborated, and the mathematical model was established with the fleet availability as the optimization objective, the cost and the safeguard probability as the constraints. Secondly, the procedure of solving multi-echelon inventory allocation model considering the influence of maintenance ratio is discussed based on the marginal analysis method. Thirdly, landing gear LRU (Line repairable units) of a typical civil aircraft were selected as the research object, multi-echelon inventory allocation was investigated by considering maintenance ratio. The analysis results show that the minimum safeguard cost and fleet availability are respectively 2759833 dollars and 0.9806, and the number of LRU of multi echelon inventory allocation are obtained under the condition of satisfying the constrained optimization. The feasibility and effectiveness of the developed method are verified by comparing the traditional analysis method. This paper provides guidance for the accurate allocation of multi echelon inventory optimization for maintenance resources on the premise of reasonable cost reduction

Abstract:
The optimal production and advertising policies for an inventory control system of multi-item multiobjective problem under a single management are formulated as an optimal control problem with resource constraints under inflation and discounting in fuzzy rough (Fu-Ro) environment. The objectives and constraints in Fu-Ro are made deterministic using fuzzy rough expected values method (EVM). Here, the production and advertisement rates are unknown and considered as control (decision) variables. The production, advertisement, and demand rates are functions of time t. Maximization of the total proceed from perfect and imperfect units and minimization of the total cost consisting of production, holding, and advertisement costs are formulated as optimal control problems and solved directly using multiobjective genetic algorithm (MOGA). In another method for solution, membership functions of the objectives are derived and the multi-objective problems are transformed to a single objective by the convex combination of the membership functions and then the problem is solved by generalized reduced gradient (GRG) method. Finally, numerical experiment and graphical representation are provided to illustrate the system. 1. Introduction From financial standpoint, an inventory represents a capital investment and a lot of researchers’ works have been done since the Second World War. Most of the classical inventory models did not take into account the effects of inflation and time value of money. This has happened mostly because of the belief that inflation and time value of money will not influence the cost and price components (i.e., the inventory policy) to any significant degree. But, during last few decades, due to high inflation and consequent sharp decline in the purchasing power of money in the developing countries like Brazil, Argentina, India, Bangladesh, and so forth, the financial situation has been changed and so it is not possible to ignore the effect of inflation and time value of money any further. Following Buzacott [1], Misra [2] extended his approaches to different inventory models with finite replenishment, shortages, and so forth, by considering the time value of money, different inflation rates for the costs. Also Lo et al. [3] developed an integrated production-inventory model with a varying rate of deterioration under imperfect production process, partial backordering, and inflation. Again, some researchers (cf. Cho [4] and others) have assumed depreciation rate of sales as a function of time, . This assumption is supported by a general fact that,

Abstract:
In this paper, a multi-item inventory model with storage space, number of orders and production cost as constraints are developed in both crisp and fuzzy environment. In most of the real world situations the cost parameters, the objective functions and constraints of the decision makers are imprecise in nature. This model is solved with shortages and the unit cost dependent demand is assumed. Hence the cost parameters are imposed here in fuzzy environment. This model has been solved by Kuhn-Tucker conditions method. The results for the model without shortages are obtained as a particular case. The model is illustrated with numerical example.

Abstract:
|In this paper, a new multi-item inventory system is considered with random demand and random lead time including m working capital and space constraints with three decision variables: order quantity, safety factor and backorder rate. The demand rate during lead time is stochastic with unknown distribution function and known mean and variance. Random constraints are transformed to crisp constraints with using the chance-constrained method. The Minimax distribution free procedure has been used to lead proposed model to the optimal solution. The shortage is allowed and the backlogging rate is dependent on the expected shortage quantity at the end of cycle. Two numerical examples are presented to illustrate the proposed solution method.

Abstract:
Support confidence framework is misleading in finding statistically meaningful relationships in market basket data. The alternative is to find strongly correlated item pairs from the basket data. However, strongly correlated pairs query suffered from suitable threshold setting problem. To overcome that, top-k pairs finding problem has been introduced. Most of the existing techniques are multi-pass and computationally expensive. In this work an efficient technique for finding k top most strongly and correlated item pairs from transaction database, without generating any candidate sets has been reported. The proposed technique uses a correlogram matrix to compute support count of all the 1- and 2-itemset in a single scan over the database. From the correlogram matrix the positive correlation values of all the item pairs are computed and top-k correlated pairs are extracted. The simplified logic structure makes the implementation of the proposed technique more attractive. We experimented with real and synthetic transaction datasets and compared the performance of the proposed technique with its other counterparts (TAPER, TOP-COP and Tkcp) and found satisfactory.