Joint pricing and inventory control for non-instantaneous deteriorating items with partial backlogging and time and price dependent demand

In this paper, a joint pricing and inventory control for non-instantaneous deteriorating items is developed. We adopt a price and time dependent demand function. Shortages is allowed and partially backlogged. The major objective is to determine the optimal selling price, the optimal replenishment schedule and the optimal order quantity simultaneously such that, the total profit is maximized. We first show that for any given selling price, optimal replenishment schedule exists and unique. Then, we show that the total profit is a concave function of price. Next, we present a simple algorithm to find the optimal solution. Finally, we solve a numerical example to illustrate the solution procedure and the algorithm.     

Inventory of differential items selling from two shops under a single management with periodically increasing demand over a finite time-horizon

Inventories of differential items including the defective ones purchased/produced in a lot and sold from two shops (primary and secondary shops) under a single management are considered here over a finite time-horizon. A primary shop receives the differential units in a lot but sells only the non-defective ones whose demand periodically increases with time and decreases during the shortage period in such a way that it comes back to the initial value at the beginning of the next cycle. Hence in this shop, shortages are allowed and fully backlogged. Moreover, at the beginning of the next cycle, the retailer purchases purely non-defective units at a higher price to meet up the shortage amount along with the usual lot of differential units for regular sale. The defective units identified at the time of selling at the primary shop are continuously transferred to the adjacent secondary shop from which the defective ones are sold at a reduced price after some rework. Normally, the price of a defective item is fixed depending upon the quantum of its defect and people go for these items if they are cheap. Hence, demand for these units is dependent on the selling price, which is again inversely proportional to the rate of defectiveness. There may be five scenarios for dealing with defective units depending upon the coincidence of the time periods at two shops. For all scenarios, problems have been mathematically formulated and solved by the use of both parametric study and a gradient-based non-linear optimisation method. The models are illustrated with the help of numerical examples.     

THE EFFECT OF TECHNOLOGICAL IMPROVEMENT ON CAPACITY EXPANSION FOR UNCERTAIN EXPONENTIAL DEMAND WITH LEAD TIMES

We formulate a model of capacity expansion that is relevant to a service provider for whom the cost of capacity shortages would be considerable but difficult to quantify exactly. Due to demand uncertainty and a lead time for adding capacity, not all shortages are avoidable. In addition, technological innovations will reduce the cost of adding capacity but may not be completely predictable. Analytical expressions for the infinite horizon expansion cost and shortages are optimized numerically. Sensitivity analyses allow us to determine the impact of technological change on the optimal timing and sizes of capacity expansions to account for economies of scale, the time value of money and penalties for insufficient capacity.     

Real Estate Values, Federal Income Taxation, and the Importance of Local Market Conditions

This article develops an income property valuation model that explicitly incorporates the effects of local market conditions. In particular, the model allows real rents to respond to a change in tax law, or to any exogenous shock to the system, with the dynamics of the rent change over time dependent upon current local supply and demand conditions and on the expected rate of economic growth in the local economy. Application of the model to an analysis of reduced capital gain taxation demonstrates that a partial reversal of TRA86's real estate provisions would disproportionately benefit those markets, and related lending institutions, which are most in need of a bolstering of real estate values.     

Lot sizes in a capacity constrained facility—a simulation study of stationary stochastic demand

This paper considers the scheduling of several different items on a single machine, in literature known as the economic lot scheduling problem, ELSP. One of the characteristics of this problem is that the demand rate is deterministic and constant. However, in a practical situation demand usually varies. In this paper we examine if a deterministic model can be used if demand is stationary stochastic. A dynamic programming approach from Bomberger (Manage. Sci. 12(11) (1966) 778) and a heuristic method from Segerstedt (Int. J. Production Econom. 59(1–3) (1999) 469) are used to calculate lot sizes for four items. The production of these items is simulated with different variations in demand rates. Our conclusion is that a deterministic model of this kind can be used in a practical situation where the demand rate is stationary stochastic, but the models must be complemented by a decision rule; which item to produce and when to produce it. In our tests the heuristic method and the dynamic programming approach perform rather similarly with respect to costs and inventory levels, but the dynamic programming approach results in more backorders when there is small variation in demand rates. This study indicates that the model used for determination of lot sizes is of less importance than the decision rule used for identification of the item to produce and when to produce it.     

Inventory decisions for substitutable products with stock-dependent demand

We study a retailer’s inventory policy for two products. The products are substitutable and have inventory dependent demand, so a higher inventory level of a product increases its sales. We model the joint effect of demand stimulation and product substitution on inventory decisions by considering a single-period, stochastic demand setting. We provide the first order optimality conditions for the profit maximizing order quantities and interpret them using marginal analysis. We also consider two heuristic solutions that separately account for either demand stimulation or product substitution. Our numerical analysis reveals that the optimal policy by appropriately using sales information that quantifies substitution and demand stimulation can produce significantly higher profits. The profit benefits are lessened under certain circumstances, such as when the two products have similar critical fractile values, suggesting that in such instances the heuristics may be used effectively.     

论中石化总公司参与进口液化气的必要性

近年来,我国液化气供需缺口日益扩大,进口ＬＰＧ已成为我国ＬＰＧ供需缺口的必要补充资源。文章分析了国ＬＰＧ的运用现状,参与进口ＬＰＧ 有利条件最后提出了６点建议采取的策略和措施。     

一种接枝氧化淀粉的环境评价及成本分析

测试接枝氧化淀粉的生物化学需氧量(BOD)和化学需氧量(COD),分析接枝氧化淀粉的成本。结果表明:接枝氧化淀粉的可生化量是0.464,在自然情况下可以完全生物降解;接枝变性淀粉浆料和PVA相比,价格每吨低3680元左右,经济效益明显。     

2011年上半年全国电力供需形势分析及全年展望

分析了2011年上半年全国宏观经济运行情况和电力供需形势。预测下半年的宏观经济走势更为复杂,电力需求增速总体平稳、电力装机增速低于用电需求增长,煤电矛盾尚未根本解决,全国电力供需形势偏紧,以缺少电力为主,并有扩大之势。提出了加强电力需求侧管理、解决煤电之间的矛盾以及构建综合能源运输体系等建议。     

Commuting Costs and Geographic Sorting in the Housing Market

The demand for housing is heavily influenced by access to employment opportunities. The cost of gasoline determines, in part, the cost of such access and therefore the relative demand across markets with varying commuting needs. Locally exogenous gasoline price movements demonstrate the causal impact of higher fuel costs on housing markets: a shift of market demand toward real estate markets with less costly commutes. Higher fuel prices increase the value of real estate with shorter commutes and easier access to driving alternatives relative to more driving dependent homes. Every incremental $1 per gallon of gasoline reduces home values by 0.143% for every additional mile relative to counterfactual markets, or $5,200 for the average home and commute. This translates into a discount rate of 6.4%, comparable to mortgage rates for the period.     

Stackelberg Independence*

The standard model of sequential capacity choices is the Stackelberg quantity leadership model with linear demand. I show that under the standard assumptions, leaders’ actions are informative about market conditions and independent of leaders’ beliefs about the arrivals of followers. However, this Stackelberg independence property relies on all standard assumptions’ being satisfied. It fails to hold whenever the demand function is non-linear, marginal cost is not constant, goods are differentiated, firms are non-identical, or there are any externalities. I show that small deviations from the linear demand assumption may make the leaders’ choices completely uninformative.     

Techno-ökonomische Bewertung von Energie-Autarkie für die Energieversorgung von Einfamilienhäusern

Many consumers currently follow the idea of energy self-sufficiency and try to contribute to meet their energy needs in order to become independent and self-sufficient from the central power supply system. In order to achieve load-oriented energy self-sufficiency the provision of energy must cover the full energy demand at any time. Against this background, in this paper the costs and potentials of a load-oriented energy self-sufficiency of single-family homes are analysed. Thereby it is differentiated between electricity-, heat- and energy self-sufficiency. The modelling is carried out with the simulation environment ?Polysun Designer“ which allows a high temporal dynamic simulation of the annual energy demand and supply.The results show that, within the investigated supply variations, the highest levels of energy self-sufficiency can be achieved by an energy supply system completely based on electricity using a combination of PV; heat pump and battery storage. Depending on the building standard, a maximum of 45 (existing buildings) and 71?% (new buildings) of the building’s energy demand can be covered with renewable energy. The economic evaluation however has shown that under present conditions, none of the investigated supply variants can compete with conventional energy supply (public grid connection + gas condensing boiler).     

Loyalty discounts and price-cost tests

We analyze, by means of a formal economic model, the use of the discount-attribution test to assess the competitive effects of loyalty discounts. (The discount-attribution test is a variant of the price-cost test, where the discount is attributed only to the share of total demand that is regarded as effectively contestable.) In the model, a dominant firm enjoys a competitive advantage over its rivals and uses market-share discounts to boost the demand for its own products. In this framework, we show that the attribution test is misleading or, at best, completely uninformative. Our results cast doubts on the applicability of price-cost tests to loyalty discount cases.     

2005年电力供需分析及2006年预测

2005年下半年开始我国电力供需矛盾开始出现缓和,作者对2005年全国电力供需情况进行了全面分析总结,并对2006年全国电力供需形势进行了分析预测,对2007年电力供需形势进行了展望。根据分析预测结果,2006年全国电力供需形势将由缺电向基本平衡过渡,自2002年以来这一轮全国性缺电局面将于2007年全面结束。     

未来十年世界石油供需格局判断

随着中国石油对外依存度逐年攀升,世界石油市场变动将对国内石油供应产生重大影响.世界存在中东、中亚—俄罗斯、非洲和中南美洲四大石油供应中心以及亚太、欧洲、北美三大石油供应洼地,北美已实现石油来源多元化,欧洲形成以中亚—俄罗斯为主、中东和非洲为辅的供应格局,亚太地区石油供应严重依赖中东.世界剩余石油资源能够满足未来十年发展需求,但不同情景的供应格局将有所差异.在高油价情景下,美洲地区能够实现石油自给,中东石油将更多地流向亚太;在低油价情景下,全球对中东地区石油的依赖将进一步增强.未来非常规石油、深水石油和伊拉克石油产量增长潜力巨大,有望成为全球石油供应增长的重要支撑.世界石油需求增幅受各国应对气候变化政策执行力度的影响而存在变数.世界石油市场全球化趋势不可逆转,中国应持续强化“走出去”战略,稳步推进石油进口来源多元化,强化关键技术装备研发,把握未来发展制高点,以全球视野保障国家石油供应安全.     

Incorporating uncertainty into a supplier selection problem

Supplier selection is an important strategic supply chain design decision. Incorporating uncertainty of demand and supplier capacity into the optimization model results in a robust selection of suppliers. A two-stage stochastic programming (SP) model and a chance-constrained programming (CCP) model are developed to determine a minimal set of suppliers and optimal order quantities with consideration of business volume discounts. Both models include several objectives and strive to balance a small number of suppliers with the risk of not being able to meet demand. The SP model is scenario-based and uses penalty coefficients whereas the CCP model assumes a probability distribution and constrains the probability of not meeting demand. Both formulations improve on a deterministic mixed integer linear program and give the decision maker a more complete picture of tradeoffs between cost, system reliability and other factors. We present Pareto-optimal solutions for a sample problem to demonstrate the benefits of the SP and CCP models. In order to describe the tradeoffs between costs and risks in an analytical form, we use multi-parametric programming techniques to more completely analyze the alternative Pareto-optimal supplier selection solutions in the CCP model. This analysis gives insights into the robustness of the solutions with respect to number of suppliers, costs and probability of not meeting demand.     

THE DEADWEIGHT LOSS OF COUPON REMEDIES FOR PRICE OVERCHARGES*

Consumers injured by price overcharges often are awarded coupons that can be used for a limited period of time to purchase the good at a price below that which prevails after the overcharge has been eliminated. Coupon remedies cause a deadweight loss by inducing excessive consumption by consumers with relatively low demand during the remedy period. The magnitude of the loss can be comparable to that caused by the price overcharge. As demand variability goes to zero, the deadweight loss from coupon remedies goes to zero. Eliminating the expiration date for the use of coupons does not eliminate the loss.     

Grid Load Contributions Through Electric Vehicles and Their Uncertainties

With the numbers of electric vehicles on the increase, their additional electricity demand can no longer be neglected. From a power systems’ perspective, it is the time dependent electricity consumption that matters. In particular, the peak demand is increased in the case of uncontrolled charging, imposing additional stress on the system. Unfortunately, since there is an absence of representative electric vehicle driving patterns, a quantification of such temporal charging requirements is challenging. To overcome this problem, we developed a detailed model, which maps combustion engine vehicles onto electric vehicle equivalents. The model’s main strengths are the consideration of the diversity within the vehicle fleet as well as the differentiation into the boundary cases of pure battery electric vehicles and plug-in hybrid electric vehicles. Applied to a German traffic study, load curves for these two cases were generated. In addition, the existing uncertainty in between was quantified using Monte Carlo method. We show that the peak energy demand through electric vehicles is much greater on working days than on weekend days. Moreover, we find that the distinction between pure and plug-in-hybrid electric vehicles matters, at least for the time being. Apart from the numerical results, the model is well suited to generate input for more sophisticated investigations of charging strategies within energy system simulations.     

Toward a Model of the Office Building Sector

High rise office buildings represent large capital outlays in very competitive markets. Investment and development decisions require careful market analysis to assure sufficient demand to lease the office space at rental rates which will make the venture financially attractive. Present methodology for analyzing future commercial real estate market conditions can at best be said to be inadequate. This methodology relies on concepts such as "market absorption" rates and "normal" vacancy rates. These concepts usually rely on accounting type and trend line techniques to provide forecasts of space demand. In this paper we provide an alternative methodology for forecasting the key variables in the office space market by developing a statistical model of supply and demand. The key variables that need to be forecasted are the stock of office space (in square feet), the flow of new office construction (in square feet), the vacancy rate (in percent), and the rent for office space (net rent per square foot).