A Linear Programming Model for an Integrated Crop and Intensive Beef Production Enterprise

In an integrated crop and intensive beef production enterprise, some of the feedstuffs used for cattle feeding are grown by the enterprise. In evaluating the performance of operations of this type, the interactions between the crop and beef production parts of the enterprise must be taken into account. A linear programming (L.P.) model of this type of enterprise is developed, with the coefficients of the animal feeding activities being derived from a dynamic programming (D.P.) model. This D.P. model is used to determine the least-cost method of feeding animals to produce a specified liveweight gain using rations formulated by L.P. from a given set of feedstuffs. This approach allows the interactions between crop and livestock production to be taken into account without the need to make assumptions about the source of feedstuffs or the rate of liveweight gain.     

A bargaining model with asymmetric information for a single supplier–single buyer problem

Banerjee’s joint economic lot size (JELS) model represents one approach to minimizing the joint total relevant cost of a buyer and a supplier by using a joint optimal order and production policy. The implementation of a jointly optimal policy requires coordination and cooperation. Should the buyer have the market power to implement his own optimal policy as that one to be used in the exchange process no incentive exists for him to choose a joint optimal policy. A joint policy can therefore only be the result of a bargaining process between the parties involved. The supplier may make some sort of concession such as a price discount or a side payment in order to influence the buyer’s order policy. A critical assumption made throughout in supply chain literature is that the supplier has complete knowledge about the buyer’s cost structure. Clearly, this assumption will seldom be fulfilled in practice. The research presented in this paper provides a bargaining model with asymmetric information about the buyer’s cost structure assuming that the buyer has the power to impose its individual optimal policy.     

Bucket brigades revisited: Are they always effective?

Previous work on the dynamics of bucket brigades has focused on systems in which workers can be ordered with respect to their speeds and where this ordering does not change throughout the line. While this assumption is valid in most environments, it may not be satisfied in some. We consider such environments and explore the conditions under which bucket brigades continue to be effective (compared to a traditional static allocation) with respect to self-balancing behavior and throughput performance. A two worker bucket brigade is studied where one worker is faster than the other over some part of the production line and slower over another part of the line. We analyze the dynamics and throughput of the bucket brigade in two environments with passing and blocking. We present the dynamics of the system in each region of the parameter space and provide insights and operating principles for the implementation and management of the bucket brigades under various scenarios.     

动态环境约束下企业的资本积累

本文讨论动态环境约束下企业的动态投资行为,拓广了文献[4]的结果.为了使讨论的问题更符合实际情况,本文假设政府设定的污染排放上限是与企业的规模大小有关,即假设污染排放上限是生产资本的函数,讨论动态环境约束下企业的最佳动态投资行为,并为政府制定污染排放政策提供依据.     

Facility location for large-scale emergencies

In the p-center problem, it is assumed that the facility located at a node responds to demands originating from the node. This assumption is suitable for emergency and health care services. However, it is not valid for large-scale emergencies where most of facilities in a whole city may become functionless. Consequently, residents in some areas cannot rely on their nearest facilities. These observations lead to the development of a variation of the p-center problem with an additional assumption that the facility at a node fails to respond to demands from the node. We use dynamic programming approach for the location on a path network and further develop an efficient algorithm for optimal locations on a general network.     

WILDLIFE LOSSES IN KENYA: AN ANALYSIS OF CONSERVATION POLICY

ABSTRACT. Despite massive conservation efforts backed bysignificant international support, Kenya has lost some 44% of its large mammal fauna over the last 17 years. This catastrophic example of resource degradation stems from a mixture of policy, institutional and market failures. Policy failures include an over‐reliance on Command and Control (prohibition on consumptive use of wildlife, prohibition on use of resources within Protected Areas) without the ability to enforce compliance; subsidies to agricultural and livestock production which, by reducing marginal production costs to below social opportunitycosts, has caused the over‐conversion of rangelands to livestock and agricultural production at the expense of conservation objectives and values; and the establishment of tourism cartels which divert wildlife generated benefits awayfrom landowners. The fundamental institutional failure is the lack of property rights and use rights of landowners over wildlife. Fundamental market failures reflect the absence of financial incentives to landowners to conserve their wildlife resource, thus setting marginal depletion costs to zero, and competing production incentives. The Kenya Wildlife Service (KWS) is reintroducing financial incentives to landowners by permitting some consumptive use of wildlife, bymaking substantial direct grants to landowners and communities who support wildlife and bysidelining the tourism cartels and encouraging private sector tourism on private land. However, investment in conservation is still being hampered by the continuing prohibition of high value activities such as sport hunting, and by over regulation and vacillation. Furthermore, positive net benefits to landowners from wildlife operations are not in themselves adequate to guarantee economic incentives to conserve the resource. First, significant negative externalities are associated with wildlife in that they add greatly to the production costs of livestock and agriculture; second, opportunity costs (in terms of foregone benefits of development) of leaving land undeveloped for conservation are gradually increasing in response to growing populations, expanding markets and new agricultural technology; and third, some policies are having the perverse impacts of creating poverty traps. Wildlife conservation policy must accordingly be much wider in scope and use a much broader range of economic, financial and market instruments, possibly including differential land use taxes, conservation subsidies and easements, and lease back agreements. Simply creating positive net benefits from wildlife is not enough.     

Local‐in‐Time Existence and Uniqueness of Solutions to the Prandtl Equations by Energy Methods

We prove local existence and uniqueness for the two‐dimensional Prandtl system in weighted Sobolev spaces under Oleinik's monotonicity assumption. In particular we do not use the Crocco transform or any change of variables. Our proof is based on a new nonlinear energy estimate for the Prandtl system. This new energy estimate is based on a cancellation property that is valid under the monotonicity assumption. To construct the solution, we use a regularization of the system that preserves this nonlinear structure. This new nonlinear structure may give some insight into the convergence properties from the Navier‐Stokes system to the Euler system when the viscosity goes to 0. © 2015 Wiley Periodicals, Inc.     

A note on interval estimation of the standard deviation of a gamma population with applications to statistical quality control

Traditional process control charts for a measurement standard deviation are based on the assumption of normality, which may not always be valid. Assuming that measurements follow a gamma distribution, we have obtained an approximate distribution of the sample variance, scaled appropriately. This approximate distribution, which happens to be another gamma model, is used to derive an interval estimate of the population standard deviation. Further, the above approximate gamma model for the sample variance can be used to develop a process control chart as demonstrated by a simulated data set.     

An economic production lot size model in an imperfect production system

The paper investigates an EPL (Economic Production Lotsize) model in an imperfect production system in which the production facility may shift from an ‘in-control’ state to an ‘out-of-control’ state at any random time. The basic assumption of the classical EPL model is that 100% of produced items are perfect quality. This assumption may not be valid for most of the production environments. More specifically, the paper extends the article of Khouja and Mehrez [Khouja, M., Mehrez, A., 1994. An economic production lot size model with imperfect quality and variable production rate. Journal of the Operational Research Society 45, 1405–1417]. Generally, the manufacturing process is ‘in-control’ state at the starting of the production and produced items are of conforming quality. In long-run process, the process shifts from the ‘in-control’ state to the ‘out-of-control’ state after certain time due to higher production rate and production-run-time.The proposed model is formulated assuming that a certain percent of total product is defective (imperfect), in ‘out-of-control’ state. This percentage also varies with production rate and production-run time. The defective items are restored in original quality by reworked at some costs to maintain the quality of products in a competitive market. The production cost per unit item is convex function of production rate. The total costs in this investment model include manufacturing cost, setup cost, holding cost and reworking cost of imperfect quality products. The associated profit maximization problem is illustrated by numerical examples and also its sensitivity analysis is carried out.     

Optimal production time and number of maintenance actions for an imperfect production system under equal-interval maintenance policy

This paper deals with the optimal production/maintenance (PM) policy for a deteriorating production system which may shift from the in-control state to the out-of-control state while producing items. The process is assumed to have a general shift distribution. Under the commonly used maintenance policy, equal-interval maintenance, the joint optimizations of the PM policy are derived such that the expected total cost per unit time is minimized. Different conditions for optimality, lower and upper bounds and uniqueness properties on the optimal PM policy are provided. The implications of another commonly used policy, to perform a maintenance action only at the end of the production run, are also discussed. Structural properties for the optimal policy are established so that an efficient solution procedure is obtained. In the exponential case, some extensions of the results obtained previously in the literature are presented. A numerical example is provided to illustrate the solution procedure for the optimal production and maintenance policy.     

Performance modeling and analysis of integrated logistic chains: An analytic framework

This paper is geared toward developing a network of inventory-queue models for the performance modeling and analysis of an integrated logistic network. An inventory-queue is a queueing model that incorporates an inventory replenishment policy for a store, which is a basic modeling element for an integrated logistic network. To achieve this objective, first, this paper presents an analytical modeling framework for integrated logistic chains, in which the interdependencies between model components are captured. Second, a network of inventory-queue models for performance analysis of an integrated logistic network with inventory control at all sites is developed. Then this paper extends the previous work done on the supply network model with base-stock control and service requirements. Instead of one-for-one base stock policy, batch-ordering policy and lot-sizing problems are considered. In practice, the assumption of uncapacitated production is often not true, therefore, GI^x/G/1 queueing analysis is used to replace the M^x/G/∞ queue based method. To include lot-sizing issue in the analysis of stores, a fixed-batch target-level production authorization mechanism is employed to explicitly obtain performance measures of the logistic chain queueing model. The validity of the proposed model is illustrated by comparing the results from the analytical performance evaluation model and those obtained from the simulation study.     

THE DYNAMICS OF AN ANIMAL—VEGETATION SYSTEM: SHEEP FARMING

The paper studies the economy and ecology of sheep farming at the farm level in a Nordic context, with a crucial distinction between the outdoors grazing season and the winter indoors feeding season, and where climate conditions fix the length of the grazing season. Two different categories of animals, ewes (adult females) and lambs, and one plant species are included in our ecological model. The farmer is assumed to maximize present‐value profit where the revenue is made up income from meat and wool production. We find that livestock cycles may represent an optimal management policy. We also show that in a possible steady state with a constant number of animals and constant vegetation quantity, slaughtering either only lambs or only ewes is optimal.     

DEA cross-efficiency evaluation under variable returns to scale

Cross-efficiency evaluation in data envelopment analysis (DEA) has been developed under the assumption of constant returns to scale (CRS), and no valid attempts have been made to apply the cross-efficiency concept to the variable returns to scale (VRS) condition. This is due to the fact that negative VRS cross-efficiency arises for some decision-making units (DMUs). Since there exist many instances that require the use of the VRS DEA model, it is imperative to develop cross-efficiency measures under VRS. We show that negative VRS cross-efficiency is related to free production of outputs. We offer a geometric interpretation of the relationship between the CRS and VRS DEA models. We show that each DMU, via solving the VRS model, seeks an optimal bundle of weights with which its CRS-efficiency score, measured under a translated Cartesian coordinate system, is maximized. We propose that VRS cross-efficiency evaluation should be done via a series of CRS models under translated Cartesian coordinate systems. The current study offers a valid cross-efficiency approach under the assumption of VRS—one of the most common assumptions in performance evaluation done by DEA.     

A Dynamic Programming Model for Pig Production

The feeding policy of a pig production unit affects both the cost of production and the weight and carcase composition of the pigs produced. Since the market value of the pigs produced is determined by the weight and composition of the carcase, feeding policy has a major influence on the economic performance of the unit. In order to evaluate possible feeding policies, the effect of feed intake on both the weight and the body composition of the growing pig must be known, and since an optimal policy will involve using least cost rations, it must be possible to determine the least cost rations to produce liveweight gains of specified body composition. A dynamic programming model to determine the optimal feeding policy to produce pigs of specified weight and carcase composition is developed using a published pig growth model which allows the formulation of the required least cost rations, and the use of this dynamic programming model is illustrated.     

Theorems that admit exceptions, including a remark on Toulmin

It is a plausible assumption that proof-novices try to make sense of the meaning of mathematical proof out of the perspective of every day thinking. In every day thinking, however, the domain of objects to which a general statement refers is not completely and definitely determined. Thus the very notion of a “universally valid statement” is not as obvious as it might seem. The phenomenon of a statement with an indefinite domain of reference can also be found in the history of mathematics when authors spoke of “theorems that admit exceptions”. Without having understood and accepted the theoretical nature of the idea of a universally valid statement the logical distinctions between, for example an implication and its converse loose their meaning for the learner. This might explain some disappointing findings of empirical research. Following a proposal by Inglis, Mejia–Ramos and Simpson it is suggested that in modelling mathematical thinking in proof situations the full scheme of Toulmin should be used including qualifications and rebuttals rather than a reduced version as is frequently done.     

Stronger upper and lower bounds for a hard batching problem to feed assembly lines

In this paper we present an Integer Programming reformulation for a hard batching problem encountered in feeding assembly lines. The study was motivated by the real process to feed the production flow through the shop floor in a leading automobile industry in Brazil. The problem consists of deciding the assignment of items to containers and the frequency of moves from the storage area to the line in order to meet demands with minimum cost. Better lower and upper bounds were obtained by a branch-and-bound algorithm based on the proposed reformulation. We also present valid inequalities that may improve such algorithm even further.     

Production-inventory control policy under warm/cold state-dependent fixed costs and stochastic demand: partial characterization and heuristics

The motivation for our study comes from some production and inventory systems in which ordering/producing quantities that exceed certain thresholds in a given period might eliminate some setup activities in the next period. Many examples of such systems have been discussed in prior research but the analysis has been limited to production settings under deterministic demand. In this paper, we consider a periodic-review production-inventory model under stochastic demand and incorporate the following fixed-cost structure into our analysis. When the order quantity in a given period exceeds a specified threshold value, the system is assumed to be in a “warm” state and no fixed cost is incurred in the next period regardless of the order quantity; otherwise the system state is considered “cold” and a positive fixed cost is required to place an order. Assuming that the unsatisfied demand is lost, we develop a dynamic programming formulation of the problem and utilize the concepts of quasi-K-convexity and non-K-decreasing to show some structural results on the optimal cost-to-go functions. This analysis enables us to derive a partial characterization of the optimal policy under the assumption that the demands follow a Pólya or uniform distribution. The optimal policy is defined over multiple decision regions for each system state. We develop heuristic policies that are aimed to address the partially characterized decisions, simplify the ordering policy, and save computational efforts in implementation. The numerical experiments conducted on a large set of test instances including uniform, normal and Poisson demand distributions show that a heuristic policy that is inspired by the optimal policy is able to find the optimal solution in almost all instances, and that a so-called generalized base-stock policy provides quite satisfactory results under reasonable computational efforts. We use our numerical examples to generate insights on the impact of problem parameters. Finally, we extend our analysis into the infinite horizon setting and show that the structure of the optimal policy remains similar.     

The robustness of the semi-Markov and delay time single-component inspection models to the Markov assumption

The context of planned preventive maintenance lends itself readilyto probabilistic modelling. Indeed, many of the published theoreticalmodels to be found in the literature adopt a Markov approach,where states are usually ‘operating’, ‘operatingat one of several levels of deterioration’, and ‘failed’.However, most of these models assume the required Markovianproperty and do not address the issue of testing the assumption,or the related task of estimating parameters. It is possiblethat data are inadequate to test the assumption, or that theMarkov property is believed to be not strictly valid, but acceptableas an approximation. In this paper we consider within a specificinspection–maintenance context the robustness of a Markov-basedmodel when the Markov assumption is not valid. This is achievedby comparing the output of an exact delay time model of an inspection–maintenanceproblem with that of a semi-Markov approximation. The importanceof establishing the vadility of the Markov property in the modellingapplication is highlighted. If the plant behaviour is seen tobe nearly Markov, in the case considered the semi-Markov modelgives a good approximation to the exact model. Conversley ifthe Markov assumption is not a good approximation, the semi-Markovmodel can lead to inappropriate advice.     

A production–inventory model in an imperfect production process

The paper develops a model to determine the optimal product reliability and production rate that achieves the biggest total integrated profit for an imperfect manufacturing process. The basic assumption of the classical Economic Manufacturing Quantity (EMQ) model is that all manufacturing items are of perfect quality. The assumption is not true in practice. Most of the production system produces perfect and imperfect quality items. In some cases the imperfect quality (non conforming) items are reworked at a cost to restore its quality to the original one. Rework cost may be reduced by improvements in product reliability (i.e., decreasing in product reliability parameter). Lower value of product reliability parameter results in increase development cost of production and also smaller quantity of nonconforming products. The unit production cost is a function of product reliability parameter and production rate. As a result, higher development cost increases unit production cost. The problem of optimal planning work and rework processes belongs to the broad field of production–inventory model which deals with all kinds of reuse processes in supply chains. These processes aim to recover defective product items in such a way that they meet the quality level of ‘good item’. The benefits from imperfect quality items are: regaining the material and value added on defective items and improving the environment protection. In this point of view, a model is introduced here to guide a firm/industry in addressing variable product reliability factor, variable unit production cost and dynamic production rate for time-varying demand. The paper provides an optimal control formulation of the problem and develops necessary and sufficient conditions for optimality of the dynamic variables. In this purpose, the Euler–Lagrange method is used to obtain optimal solutions for product reliability parameter and dynamic production rate. Finally, numerical examples are given to illustrate the proposed model.     

Generalizations of common ILF models

In Germany (and various other countries) a specific ILF model, which was proposed by Riebesell in 1936, is frequently used for exposure rating in liability insurance and reinsurance. This model is based on the assumption that the doubled limits surcharge (DLS) – i.e. the percentage surcharge on the premium for doubling policy limits – does not depend on the policy limit. The drawback of this method is its lack of flexibility with respect to the corresponding severity distribution. In this paper we analyze the following generalizations of this concept which offer more flexibility regarding the severity: stepwise reduction of the DLS, continuously decreasing DLSs and construction of an ILF formula based on the DLS at a certain policy limit and the tail of a severity distribution.