bayesian single and double variable sampling plans for the weibull distribution with censoring the sampling inspection problem is one of the main research topics in quality control in this paper we employ bayesian decision theory to study single and double variable sampling plans for the weibull distribution with type ii censoring a general loss function which includes the sampling cost the time consuming cost the salvage value and the after sales cost is proposed to determine the bayes risk and the corresponding optimal sampling plan explicit expressions for the bayes risks for both single and double sampling plans are derived respectively numerical examples are given to illustrate the effectiveness of the proposed method comparisons between single and double sampling plans are made and sensitivity analysis is performed

an interpolating by pass to pareto optimality in intuitionistic fuzzy technique for a eoq model with time sensitive backlogging abstract this article fuzzyfies eoq crisp model with backlogged while demand of the customers varies with selling price and promotional effort the demand rate in stock out situation decreases with duration of the shortage period and it comes back to its initial rate since promotional effort continues the cost function consists of set up cost inventory cost shortage cost and cost for promotional effort the coefficient vectors of the concerned minimization cost function are considered as fuzzy numbers which are transformed into interval numbers then the interval objective function has been transformed into a classical multi objective eoq model using intuitionistic fuzzy technique a comparative study on pareto optimality and optimality under lagrange s interpolating polynomial function has been made illustrating numerical example

an eoq model of homogeneous products while demand is salesmen s initiatives and stock sensitive the author develops an inventory model to determine the retailer s optimal order quantity for homogeneous products it is assumed that the amount of display space is limited and the demand of the products is dependent on the display stock level where a huge stock of one product has a negative effect on the other product also the replenishment rate depends on the level of stock of the items the objective of the model is to maximize the profit function considering the effect of inflation and time value of money by pontryagin s maximal principles the stability analysis of the concerned dynamical system has been carried out analytically as well as numerically

interactive image segmentation based on synthetic graph coordinates in this paper we propose a framework for interactive image segmentation the goal of interactive image segmentation is to classify the image pixels into foreground and background classes when some foreground and background markers are given the proposed method minimizes a min max bayesian criterion that has been successfully used on image segmentation problem and it consists of several steps in order to take into account visual information as well as the given markers without any requirement of training first we partition the image into contiguous and perceptually similar regions superpixels then we construct a weighted graph that represents the superpixels and the connections between them an efficient algorithm for graph clustering based on synthetic coordinates is used yielding an initial map of classified pixels this method reduces the problem of graph clustering to the simpler problem of point clustering instead of solving the problem on the graph data structure as most of the known algorithms from literature do finally having available the data modeling and the initial map of classified pixels we use a markov random field mrf model or a flooding algorithm to get the image segmentation by minimizing a min max bayesian criterion experimental results and comparisons with other methods from the literature are presented on lhi gulshan and zhao datasets demonstrating the high performance and accuracy of the proposed scheme

chaos in the gylden problem we consider the gylden problem a perturbation of the kepler problem via an explicit function of time for certain general classes of planar periodic perturbations after proving a poincare melnikov type criterion we find a manifold of orbits in which the dynamics is given by the shift automorphism on the set of bi infinite sequences with infinitely many symbols we achieve the main result by computing the melnikov integral explicitly

random effects weibull regression model for occupational lifetime abstract with great interest we read the recent publication of sohn et al sohn s y chang i s moon t h 2007 random effects weibull regression model for occupational lifetime european journal of operational research 179 124 131 on a weibull regression model with random effects for modelling occupational lifetime we congratulate sohn and colleagues on their comprehensive and clearly written paper nevertheless we would like to comment on two points the first regarding the moments of the underlying weibull distribution the second regarding the relations of sohn s model to the class of frailty models

interactive image segmentation via kernel propagation abstract in this paper we propose a new approach to interactive image segmentation via kernel propagation kp called kp cut the key to success in interactive image segmentation is to preserve characteristics of the user s interactive input and maintain data coherence effectively to achieve this we employ kp which is very effective in propagating the given supervised information into the entire data set kp first learns a small size seed kernel matrix and then propagates it into a large size full kernel matrix it is based on a learned kernel and thus can fit the given data better than a predefined kernel based on kp we first generate a small size seed kernel matrix from the user s interactive input then the seed kernel matrix is propagated into the full kernel matrix of the entire image during the propagation foreground objects are effectively segmented from background experimental results demonstrate that kp cut effectively extracts foreground objects from background and outperforms the state of the art methods for interactive image segmentation

interactive image segmentation using probabilistic hypergraphs this paper introduces a novel interactive framework for segmenting images using probabilistic hypergraphs which model the spatial and appearance relations among image pixels the probabilistic hypergraph provides us a means to pose image segmentation as a machine learning problem in particular we assume that a small set of pixels which are referred to as seed pixels are labeled as the object and background the seed pixels are used to estimate the labels of the unlabeled pixels by learning on a hypergraph via minimizing a quadratic smoothness term formed by a hypergraph laplacian matrix subject to the known label constraints we derive a natural probabilistic interpretation of this smoothness term and provide a detailed discussion on the relation of our method to other hypergraph and graph based learning methods we also present a front to end image segmentation system based on the proposed method which is shown to achieve promising quantitative and qualitative results on the commonly used grabcut dataset

dynamic pricing of seasonal goods with spot and forward purchase demands this paper deals with the problem of jointly determining the order size and dynamic prices for a perishable inventory system over a finite time planning horizon when firms simultaneously provide customers with a prompt delivery option and a delivery schedule option customers are segmented into two types namely spot purchase customers and the forward purchase customers demands for both types of customers are assumed to be time and price dependent the decision maker of the inventory system is assumed to apply pricing policies to stimulate demand to improve revenues under the condition that customers with forward purchases may cancel their orders a mathematical model is developed to find the optimal number of price settings the optimal dynamic prices and the order quantity a solution procedure is found to determine the optimal decisions

analytic integrability of a chua system we consider the system x a z a1x3 a2x2 bx y z z b1x y b2z where a and b are parameters and b1 7 10 b2 6 25 a1 44 3 and a2 41 2 we analyze the existence of local and global analytic first integrals

an optimal inventory replenishment policy for a deteriorating item with time quadratic demand and time dependent partial backlogging with shortages in all cycles abstract the paper deals with an optimal inventory replenishment policy for a deteriorating item considering time quadratic demand and time dependent partial backlogging which depends on the length of the waiting time for the next replenishment over a finite time horizon and variable replenishment cycle the model is solved analytically to obtain the optimal solution of the problem it is then illustrated with the help of numerical examples

random walks for image segmentation a novel method is proposed for performing multilabel interactive image segmentation given a small number of pixels with user defined or predefined labels one can analytically and quickly determine the probability that a random walker starting at each unlabeled pixel will first reach one of the prelabeled pixels by assigning each pixel to the label for which the greatest probability is calculated a high quality image segmentation may be obtained theoretical properties of this algorithm are developed along with the corresponding connections to discrete potential theory and electrical circuits this algorithm is formulated in discrete space i e on a graph using combinatorial analogues of standard operators and principles from continuous potential theory allowing it to be applied in arbitrary dimension on arbitrary graphs

hyperbolicity transversality and analytic first integrals abstract let a be a normally hyperbolic compact invariant manifold of an analytic diffeomorphism f of an analytic manifold m we assume that the stable and unstable manifold of a intersect transversally in an admissible way the dynamics on a is ergodic and the modulus of the eigenvalues associated to the stable and unstable manifold respectively satisfy a non resonance condition in the case where a is a point or a torus we prove that the discrete dynamical system associated to f does not admit an analytic first integral the proof is based on a triviality lemma which is of combinatorial nature and a geometrical lemma the same techniques allow us to prove analytic non integrability of hamiltonian systems having arnold diffusion in particular using results of xia we prove analytic non integrability of the elliptic restricted three body problem as well as the planar three body problem

an economic production lot size model with deteriorating items stock dependent demand inflation and partial backlogging in this paper we present an optimization framework to derive optimal production over a fixed planning horizon for items with a stock dependent demand rate and under inflationary conditions we consider a perishable item that follows a two parameter weibull distribution shortage is allowed and partially backlogged at a fixed rate a numerical example is taken up to illustrate the solution procedure and sensitivity analysis of the optimal solution with respect to the parameters of the system is carried out

price determination for an eoq model for deteriorating items under perfect competition the problem of price determination for an eoq model under perfect competition is of central importance in the field of inventory control and management especially for such kind of models which study the dynamics of the market economy over time in this paper an attempt has been made to analyze and compute the price of a unit item of inventory for an eoq model for deteriorating items under the perfect competition as an important market structure along with the optimization technique the marginal revenue and marginal cost approach has been employed to determine the price of a unit item of inventory the present work is presumably believed to provide theoretical as well as applicable insight for marketing experts and inventory managers engaged in this field

finding optimal s s policies is about as simple as evaluating a single policy in this paper a new algorithm for computing optimal s s policies is derived based upon a number of new properties of the infinite horizon cost function c s s as well as a new upper bound for optimal order up to levels s and a new lower bound for optimal reorder levels s the algorithm is simple and easy to understand its computational complexity is only 2 4 times that required to evaluate a specific single s s policy the algorithm applies to both periodic review and continuous review inventory systems

an efficient algorithm for computing optimal s s policies this paper presents an algorithm to compute an optimal s s policy under standard assumptions stationary data well behaved one period costs discrete demand full backlogging and the average cost criterion the method is iterative starting with an arbitrary given s s policy and converging to an optimal policy in a finite number of iterations any of the available approximations can thus be used as an initial solution each iteration requires only modest computations also a lower bound on the true optimal cost can be computed and used in a termination test empirical testing suggests very fast convergence

fast approximate energy minimization via graph cuts many tasks in computer vision involve assigning a label such as disparity to every pixel a common constraint is that the labels should vary smoothly almost everywhere while preserving sharp discontinuities that may exist e g at object boundaries these tasks are naturally stated in terms of energy minimization the authors consider a wide class of energies with various smoothness constraints global minimization of these energy functions is np hard even in the simplest discontinuity preserving case therefore our focus is on efficient approximation algorithms we present two algorithms based on graph cuts that efficiently find a local minimum with respect to two types of large moves namely expansion moves and swap moves these moves can simultaneously change the labels of arbitrarily large sets of pixels in contrast many standard algorithms including simulated annealing use small moves where only one pixel changes its label at a time our expansion algorithm finds a labeling within a known factor of the global minimum while our swap algorithm handles more general energy functions both of these algorithms allow important cases of discontinuity preserving energies we experimentally demonstrate the effectiveness of our approach for image restoration stereo and motion on real data with ground truth we achieve 98 percent accuracy

fine structured object segmentation via neighborhood propagation this paper presents a novel method for the challenging task of fine structured fs object segmentation the task is formulated as a label propagation problem on an affinity graph the proposed method has mainly three advantages first to enhance the completeness and connectivity of fs objects we introduce a novel neighborhood system combining both local and nonlocal connections with a robust scheme for edge weight calculation second appearance models are explicitly incorporated into the energy function as a term of region cost this helps to further preserve the connectivity of the fine parts for which the label information is hard to propagate correctly via neighboring pixels alone third the resulting energy minimization problem has a closed form solution with global optimum guaranteed showing an advantage over the fs object segmentation methods that suffer from np hardness to enrich the evaluation of fs object segmentation methods we created a new challenging data set it consists of 100 natural images involving diverse fs objects with accurately hand labeled ground truth extensive experimental results demonstrate that our method is effective in handling fs objects and achieves the state of the art performance highlightswe propose a method for fine structured object segmentation via label propagation a novel affinity graph combining local and nonlocal connections is constructed we incorporate appearance models as labeling preference for the label propagation the energy minimization is achieved with a globally optimal closed form solution extensive experimental results demonstrate the effectiveness of our method

an epq model with partial backorders considering two backordering costs abstract we propose an epq model with partial backorders considering linear and fixed backordering costs time intervals rather than ordering size and backordering level are used as decision variables to derive the closed form optimal solution our approach analyzes different optimal inventory policies and decides whether shortage period should be scheduled in addition a critical backordering rate is derived to determine the feasible optimal solution the numerical example is provided to illustrate the solution procedure

an epq model with inflation in an imperfect production system in this paper a production inventory model is considered for stochastic demand with the effect of inflation generally every manufacturing system wants to produce perfect quality items however due to real life problems labor problems machine breakdown etc a certain percentage of products are of imperfect quality the imperfect items are reworked at a cost the lifetime of a defective item follows a weibull distribution due to the production of imperfect quality items a product shortage occurs the profit function is derived by using both a general distribution of demand and the uniform rectangular distribution of demand computational experiments along with graphical illustrations are presented to discuss the optimality of the probability functions

arnold diffusion and oscillatory solutions in the planar three body problem abstract in this paper the following results concerning the newtonian three body problem are obtained 1 arnold diffusion exists in the planar three body problem as conjectured by v 1 arnold 1964 dokl acad nauk sssr 156 9 2 the oscillatory solutions as well as capture and escaping solutions among other classes of chaotic solutions exist in the three body problem 3 a special and interesting phenomenon which we call the pseudo arnold diffusion arises near infinity in the three body problem 4 as a result of the existence of arnold diffusion the planar three body problem is non integrable and there are no additional real analytic integrals besides the known ones

optimization models and a ga based algorithm for stochastic time cost trade off problem in real life projects both the trade off between the project cost and the project completion time and the uncertainty of the environment are considerable aspects for decision makers however the research on the time cost trade off problem seldom concerns stochastic environments besides optimizing the expected value of the objective is the exclusive decision making criterion in the existing models for the stochastic time cost trade off problem in this paper two newly developed alternative stochastic time cost trade off models are proposed in which the philosophies of chance constrained programming and dependent chance programming are adopted for decision making in addition a hybrid intelligent algorithm integrating stochastic simulations and genetic algorithm is designed to search the quasi optimal schedules under different decision making criteria the goal of the paper is to reveal how to obtain the optimal balance of the project completion time and the project cost in stochastic environments

continuous review inventory model in mixed fuzzy and stochastic environment in this paper we consider a continuous review inventory system where fuzziness and randomness appear simultaneously into an optimization setting since demand plays an important role in such type of inventory systems we develop a model in a mixed environment by incorporating fuzzy random variable as customer demand after fuzzifying the random lead time demand we consider the annual average demand as a fuzzy random variable we provide an elegant methodology to determine the optimal order quantity and reorder point such that the total expected annual cost in the fuzzy sense has a minimum value since the expected value of a fuzzy random variable is a fuzzy quantity a method of ranking fuzzy numbers using their possibilistic mean values is adopted to achieve the optimal solution a numerical example is presented to illustrate the proposed model

two storage inventory problem with dynamic demand and interval valued lead time over finite time horizon under inflation and time value of money a finite time horizon inventory problem for a deteriorating item having two separate warehouses one is a own warehouse ow of finite dimension and other a rented warehouse rw is developed with interval valued lead time under inflation and time value of money due to different preserving facilities and storage environment inventory holding cost is considered to be different in different warehouses the demand rate of item is increasing with time at a decreasing rate shortages are allowed in each cycle and backlogged them partially shortages may or may not be allowed in the last cycle and under this circumstance there may be three different types of model here it is assumed that the replenishment cycle lengths are of equal length and the stocks of rw are transported to ow in continuous release pattern for each model different scenarios are depicted depending upon the re order point for the next lot representing the lead time by an interval number and using the interval arithmetic the single objective function for profit is changed to corresponding multi objective functions these functions are maximized and solved by fast and elitist multi objective genetic algorithm femga the models are illustrated numerically and the results are presented in tabular form

multi item imperfect production lot size model with hybrid number cost parameters in this study we have developed a multi item finite production lot size model with reworking of imperfect quality items when production stops defected items are assumed to rework at a constant rate the cost parameters in this model are taken here as hybrid numbers i e some of the costs are fuzzy numbers as well as random variables then the model is converted into a multi objective geometric programming gp problem a numerical example is given to support the problem a sensitivity analysis has given to study the nature of the objective functions

an eoq model with delay in payments and stock dependent demand in the presence of imperfect production abstract in real life situation supplier generally offers a delay period to the retailer to buy more in this connection a mathematical model is considered to investigate the retailer s optimal replenishment policy under permissible delay in payment with stock dependent demand within the eoq economic order quantity framework most of the eoq models are considered with infinite replenishment rate in this article the model is considered with finite replenishment rate under progressive payment scheme with the production of defective items within the cycle time the mathematical models have been derived for obtaining the optimal cycle time so that the annual total relevant cost is minimized numerical examples along with graphical representation and sensitivity analysis are provided to illustrate the model

price sensitive demand for perishable items an eoq model abstract this paper develops a finite time horizon deterministic eoq economic order quantity model where the rate of demand decreases quadratically with selling price prices at different periods are considered as decision variables the objective is to find the optimal ordering quantity and optimal sales prices that maximizes the vendor s total profit the results are discussed with numerical examples sensitivity analysis of the optimal solution with respect to the key parameters of the system is carried out

a note on optimal replenishment policy for imperfect quality emq model with rework and backlogging a recent article on optimal replenishment policy of imperfect emq model by chiu s w chiu optimal replenishment policy for imperfect quality emq model with rework and backlogging applied stochastic models in business and industry 23 2007 165 178 used mathematical modeling and differential calculus to derive the optimal ordering policy that minimizes overall costs this paper presents a straightforward algebraic approach to replace the use of calculus on the cost function for determining the optimal replenishment solutions as well as the long run average production inventory costs for such an imperfect emq model the algebraic method presented in this paper may enable students or practitioners with little or no knowledge of calculus to learn or to manage with ease the real life manufacturing systems

the sharma parthasarathy stochastic two body problem we study the sharma parthasarathy stochastic two body problem introduced by sharma and parthasarathy in dynamics of a stochastically perturbed two body problem proc r soc a 463 979 1003 2007 in particular we focus on the preservation of some fundamental features of the classical two body problem like the hamiltonian structure and first integrals in the stochastic case numerical simulations are performed which illustrate the dynamical behaviour of the osculating elements as the semi major axis the eccentricity and the pericenter we also derive a stochastic version of gauss s equations in the planar case

optimal price and lot size determination for a perishable product under conditions of finite production partial backordering and lost sale the paper describes an eoq model of a perishable product for the case of price dependent demand partial backordering which depends on the length of the waiting time for the next replenishment and lost sale the model is solved analytically to obtain the optimal price and size of the replenishment in the model the customers are viewed to be impatient and a fraction of the demand is backlogged this fraction is a function of the waiting time of the customers in most of the inventory models developed so far researchers considered that inventory accumulates at the early stage of the inventory and then shortage occurs this type of inventory is called ifs inventory followed by shortage policy in the present model we consider that shortage occurs before the starting of inventory we have proved numerically that instead of taking ifs if we consider sfi shortage followed by inventory policy we would get better result i e a higher profit the model is extended to the case of non perishable product also the optimal solution of the model is illustrated with the help of a numerical example

optimal selling price and lotsize with time varying deterioration and partial backlogging the article deals with an eoq economic order quantity model over an infinite time horizon for perishable items where demand is price dependent and partial backorder is permitted the rate of deterioration is taken to be time proportional and it is assumed that shortage occurs at starting of the inventory cycle based on the partial backlogging and lost sale cases the author develops the criterion for the optimal solution for the replenishment schedule and proves the optimal ordering policy is unique moreover the article suggests to new functions regarding price dependent demand and time varying deterioration rate finally numerical examples are illustrated to test the model in various issues