Global plant capacity and product allocation with pricing decisions

Trade-offs in global manufacturing decisions involve markets, resource costs, trade-barriers, currency exchange rates, joint ventures and investments. We develop a model that optimizes plant investment decisions, while ensuring that the plant investment overhead is optimally absorbed by products produced from that plant. The model also, simultaneously, determines prices by products and countries. The special structure of the model is exploited to construct a fast solution procedure. The model is used to study the implications of labor cost, transportation cost, demand, and import tariff on production quantities, investment, and overhead absorption pattern. Implications of changes in other global parameters such as local-content rule, local taxes, size of the market in a country, and long-term exchange rates are also studied.     

Optimal production,purchasing and pricing: A differential game approach

This paper deals with a problem of determining optimal production and pricing policies of a manufacturing firm which is supplying a retailer, The latter faces a price-dependent demand function towards the final consumers and wishes to determine optimal purchasing and pricing policies. Both firms carry inventories and backlogging is permitted. The problem is modelled as a two-player nonzero-sum differential game with the inventory levels as the state variables. The controls are the rates of production and purchasing as well as the prices. Assuming linear production costs, but convex ordering and holding costs, open-loop Nash controls are characterized by using switching point analysis as well as phase diagrams.     

Bundling retail products: Models and analysis

We consider the impact of bundling products on retail merchandising. We consider two broad classes of retail products: basic and fashion. For these product classes, we develop models to calculate the optimal bundle prices, order quantities, and profits under bundling. We use this analysis to establish conditions and insights under which bundling is profitable. Our analysis confirms that bundling profitability depends on individual product demands, bundling costs, and the nature of the relationship between the demands of the products to be bundled. We also provide detailed numerical examples.     

MODELING THE EFFECT OF INSTITUTIONAL CONSTRAINTS ON SHORT-RUN TIMBER SUPPLY ON PUBLIC LAND: A CASE STUDY OF QUOTA HOLDERS IN ALBERTA

The short-run timber supply behavior of quota holders is investigated in the face of institutional constraints and fixed stumpage prices. A dynamic optimization technique is used to predict production and estimate shadow prices of processing capacity constraints and annual allowable cut restrictions. Models for large, medium, and small tenure holders are formulated reflecting the different cost structures of different sized firms. Results indicate that all categories of quota holders incur substantial costs due to institutional constraints, and that eliminating both types of constraints simultaneously reduces costs much more than the combined savings from eliminating each type of constraint individually.     

Marginal cost pricing and revenue reconciliation for electricity

This paper demonstrates how mathematical programming can be used to calculate efficient prices of electricity when demand fluctuates over time and where production comes from different types of plants. It is shown that prices have to be set according to marginal costs and differentiated between peak and off-peak load.Furthermore, the paper concerns the use of reconciliation methods for those cases where producers' surplus will be far above what might be considered as a fair rate of return. Here it is shown that it is extremely important to let the energy charges follow the marginal costs, while any modification of the efficient price should be directed to changes in fixed charges.     

Supporting offshoring and nearshoring decisions for mass customization manufacturing processes

Offshore countries attract companies for a possible relocation of production processes through extremely low worker wages. Particularly, mass production processes seem to be highly appropriate for a relocation. However, while the impact of wage reductions can be directly estimated, an appropriate determination of additional cost consequences proves to be a complex task. For instance, on account of lower education standards and higher fluctuation rates, the average worker skills in offshore countries are often significantly lower than in high-wage countries like the United States. In order to appropriately analyze and evaluate the resulting tradeoff between wages and worker skills for mass customization manufacturing systems, this paper introduces a new approach that comprises a detailed mixed-model assembly line balancing. This approach provides a direct comparison of the estimated variable manufacturing costs by generating a country-dependent line layout for all competing locations. In order to validate the efficiency of the balancing approach and, in particular, derive general implications for management, several test series with various country configurations were executed. First, by attaining improvement rates of up to 40%, the capability of a generated Tabu Search procedure for finding appropriate line layouts was proven. Second, as the main result, the complexity of the variant program was identified as a crucial factor for offshoring decisions since it substantially affects variable manufacturing costs. This was particularly proven for countries with low worker skills, which attract offshoring/nearshoring through exceptionally low labor costs. Hence, companies that consider outsourcing production systems to those countries are strongly hold to examine these decisive effects thoroughly. Regarding this, offshoring becomes very promising for manufacturing processes characterized by a moderate variant complexity level.     

First principles versus artificial neural network modelling of a solar desalination system with experimental validation

ABSTRACT

The present study mainly focuses on enhancing the performance of solar still unit using solar energy through cylindrical parabolic collector and solar panels. A 300 W solar panel is used to heat saline water by thermal elements outside the solar still unit. Solar panels are cooled during the hot hours of the day; thus, reducing their temperature may lead to an increase in solar panel efficiency followed by an increase in the efficiency of the solar still unit. The maximum amount of freshwater used in the experiment was 2.132 kg/day. The experiments were modelled using ANNs. Based on neural network simulation results, there is a significant correlation between experimental data and neural network modelling. This paper compares experimental data with data obtained from mathematical modelling and ANNs. As a conclusion, the artificial neural network prediction has been more accurate than the simplified first principles model presented.     

A comparison of shadow prices and reimbursement rates of hospital services

The purpose of this paper is to calculate shadow prices of hospital services and compare them to the reimbursement rates those hospitals receive. These shadow prices are calculated by estimating a multiple-output distance function and applying a dual Shephard's lemma, a technique suggested by Färe and Grosskopf [8]. In contrast to cost functions, distance functions require no price data and do not presume cost minimization. We apply this technique to a sample of California hospitals operating in 1986. We find that hospitals engaged in selective contracting for Medi-Cal patients exhibit closer agreement between relative shadow prices and relative reimbursement rates (Medi-Cal relative to private patients) than noncontracting hospitals.Contact author.     

Integrated planning of transportation and recycling for multiple plants based on process simulation

By-products accrue in all stages of industrial production networks. Legal requirements, shortening of primary resources and their increasing prices make their recycling more and more important. For the re-integration into the economic cycle the scope of common supply chain management is enlarged and so-called closed-loop supply chains with adapted and new planning tasks are developed. In process industries this requires a detailed modelling of the recycling processes. This is of special relevance for operational planning tasks in which an optimal usage of a given production system is envisaged. This contribution presents an integrated planning approach for a real-world case study from the zinc industry to achieve such an adequate process modelling. We consider the planning problem of a company that operates four metallurgical recycling plants and has to allocate residues from different sources to these recycling sites. The allocation determines the raw material mix used in the plants. This blending has an effect on the transportation costs and the costs and revenues of the individual technical processes in the recycling plants. Therefore in this problem transportation and recycling planning for multiple sites have to be regarded in an integrated way. The necessary detailed process modelling is achieved by the use of a flowsheet process simulation system to model each recycling plant individually. The models are used to derive linear input–output functions by multiple linear regression analyses. These are used in an integrated planning model to calculate the decision-relevant input and output flows that are dependent upon the allocation of the residues to the recycling sites. The model is embedded in a decision support system for the operational use. An example application and sensitivity analyses demonstrate and validate the approach and its potentials. The approach is transferable to other recycling processes as well as to other processes in process industries.     

Profit Maximization-The ELS Model under Varying Mark-Up and Different Cost Structures

This paper discusses the influence of mark-up of prices, costs due to damaged goods and advertising expenditure related to the ELS inventory model with discrete units. A numerical example is also given, with its detailed sensitivity analysis.     

Reinforcement learning for joint pricing,lead-time and scheduling decisions in make-to-order systems

The paper investigates a problem faced by a make-to-order (MTO) firm that has the ability to reject or accept orders, and set prices and lead-times to influence demands. Inventory holding costs for early completed orders, tardiness costs for late delivery orders, order rejection costs, manufacturing variable costs, and fixed costs are considered. In order to maximize the expected profits in an infinite planning horizon with stochastic demands, the firm needs to make decisions from the following aspects: which orders to accept or reject, the trade-off between price and lead-time, and the potential for increased demand against capacity constraints. We model the problem as a Semi-Markov Decision Problem (SMDP) and develop a reinforcement learning (RL) based Q-learning algorithm (QLA) for the problem. In addition, we build a discrete-event simulation model to validate the performance of the QLA, and compare the experimental results with two benchmark policies, the First-Come-First-Serve (FCFS) policy and a threshold heuristic policy. It is shown that the QLA outperforms the existing policies.     

Determination of optimal penalties for antitrust violations in a dynamic setting

We analyze a differential game describing the interactions between a firm that might be violating competition law and the antitrust authority. The objective of the authority is to minimize social costs (loss in consumer surplus) induced by an increase in prices above marginal costs. It turns out that the penalty schemes which are used now in EU and US legislation appear not to be as efficient as desired from the point of view of minimization of consumer loss from price-fixing activities of the firm. In particular, we prove that full compliance behavior is not sustainable as a Nash Equilibrium in Markovian strategies over the whole planning period, and, moreover, that it will never arise as the long-run steady-state equilibrium of the model. We also investigate the question which penalty system enables us to completely deter cartel formation in a dynamic setting. We found that this socially desirable outcome can be achieved in case the penalty is an increasing function of the degree of offence and is negatively related to the probability of law enforcement.     

回收率依赖价格的再制造EPQ模型研究

研究了考虑回收率依赖于回收品价格,并带有废弃处理的制造和再制造混合系统的(1,R)和(M,1)EPQ模型.在模型中,采用新产品的制造和回收产品的再制造两种方式来满足客户的需要,回收产品部分用于再制造,其余作为废弃处理;总平均成本包括与回收产品、可销售产品有关的库存持有成本,与制造和再制造有关的生产成本和固定成本,与回收品及制造所需原材料的采购成本以及废弃处理成本.模型给出最优生产策略及总平均成本的表达式.算例验证了所建模型的计算方法,并分析了新引人决策变量p(回收产品单价占制造新产品所需原料价格的比例对总平均成本的变化率的影响.     

A learning curve model with knowledge depreciation

Empirical studies in several industries have verified that unit costs decline as organizations gain experience or knowledge in production, which is referred to as the learning curve effect. In the past two decades, there has also been analytical work on the relationship between a firm's learning curve effects and its pricing and output decisions. Learning rates differ significantly across firms in the same industry and recent empirical evidence has shown that knowledge depreciation may be an important reason for these differences. We propose and analyze a learning curve model with knowledge depreciation and provide several new insights. First, we show that there exists a steady state where knowledge level and unit cost remain constant over time and there exists an optimal path to this steady state. Many empirical researchers have observed this ‘plateau’ phenomenon, whereby unit costs decline but reach saturation after some time. While this has been traditionally modeled exogenously in the learning curve literature by assuming that cost reduction stops at some level of knowledge through a convex, decreasing unit cost function, we provide an alternative endogenous explanation. We are also able to show that, unlike in the model without knowledge depreciation, the production rate along the optimal path to the steady state may decrease over time. Also, the knowledge level along the optimal path may actually decline over time. Finally, we show that the optimal production rate decreases at higher interest rates and increases at higher knowledge depreciation rates. In turn, this implies that a high interest rate environment discourages firms from achieving high knowledge levels and results in higher prices. On the other hand, higher knowledge depreciation rates result in higher production rates and lower prices.     

Elementary Theory of Optimal Silo Storage Design

This study indicates a method for calculating an economic division of warehouses into compartments when different varieties have to be stored simultaneously and separately. The study deals with cases where the total storage capacity demand and the number of varieties are known and fixed, but where the storage capacity demand of each variety is unknown. Problems of this nature exist in the preliminary designing of grain silos, fleets of transport vehicles, utensils in public kitchens, etc. If the warehouse capacity can cope with the total storage capacity demand, but the number of compartments is insufficient, it is possible that part of the material to be stored cannot be accommodated, although certain compartments may only be partly filled; this will be due to the impossibility of storing different varieties together. The materials will have to be stored in other warehouses, at a higher charge per capacity unit than that of the warehouse in question.The division of the warehouse into a large number of compartments will assure storage of most, if not all, the material. On the other hand, increase in the number of compartments (and installations) makes for increased investment in transport installation, partitions and additional storage capacity to compensate for space taken up by these partitions and installations.The object of this study is to introduce a method for calculating the optimal division of a warehouse into compartments, so that the annual costs of storage and capital investment are minimized.It is possible-by introducing not very restrictive statistical assumptions-to calculate the annual costs of storing excluded material elsewhere for different modes of partitioning a warehouse into compartments. The annual building cost of the warehouse is calculated in the ordinary way.In this study a solution is offered for the partitioning of a warehouse into equal compartments. It is to be expected that the extension of this solution to cases of the partition into compartments, differing from each other as to storage capacity, will tend to lower costs.     

基于空间过滤的制造业劳动生产率地区收敛性估计

有别于现有针对整体经济的收敛性研究,在制造业层面估计了劳动生产率的地区收敛性.在构建动态经济空间权重矩阵的基础上,检验发现制造业劳动生产率存在显著的空间依赖性.使用空间过滤数据和动态面板收敛模型的估计结果表明,制造业劳动生产率的增长在1988-1997年以年均约为3%的速度扩散,而在1998-2005年以年均约4.5%的速度收敛.     

A fractional credit model with long range dependent default rate

Motivated by empirical evidence of long range dependence in macroeconomic variables like interest rates we propose a fractional Brownian motion driven model to describe the dynamics of the short and the default rate in a bond market. Aiming at results analogous to those for affine models we start with a bivariate fractional Vasicek model for short and default rate, which allows for fairly explicit calculations. We calculate the prices of corresponding defaultable zero-coupon bonds by invoking Wick calculus. Applying a Girsanov theorem we derive today’s prices of European calls and compare our results to the classical Brownian model.     

On the Modeling of CO2 EUA and CER Prices of EU‐ETS for the 2008–2012 Period

Increased consumption of fossil fuels in industrial production has led to a significant elevation in the emission of greenhouse gases and to global warming. The most effective international action against global warming is the Kyoto Protocol, which aims to reduce carbon emissions to desired levels in a certain time span. Carbon trading is one of the mechanisms used to achieve the desired reductions. One of the most important implications of carbon trading for industrial systems is the risk of uncertainty about the prices of carbon allowance permits traded in the carbon markets. In this paper, we consider stochastic and time series modeling of carbon market prices and provide estimates of the model parameters involved, based on the European Union emissions trading scheme carbon allowances data obtained for 2008–2012 period. In particular, we consider fractional Brownian motion and autoregressive moving average–generalized autoregressive conditional heteroskedastic modeling of the European Union emissions trading scheme data and provide comparisons with benchmark models. Our analysis reveals evidence for structural changes in the underlying models in the span of the years 2008–2012. Data‐driven methods for identifying possible change‐points in the underlying models are employed, and a detailed analysis is provided. Our analysis indicated change‐points in the European Union Allowance (EUA) prices in the first half of 2009 and in the second half of 2011, whereas in the Certified Emissions Reduction (CER) prices three change‐points have appeared, in the first half of 2009, the middle of 2011, and in the second half of 2012. These change‐points seem to parallel the global economic indicators as well. Copyright © 2016 John Wiley & Sons, Ltd.     

The informational content of subordinated debt and equity prices in the presence of bankruptcy costs

The paper extends the contingent valuation framework of Black and Cox [J. Finance 31(2) (1976) 351] to value subordinated debt by explicitly incorporating bankruptcy costs in the model. We show that the information from subordinated debt prices is complementary to the information from the equity prices only when the bankruptcy costs are taken into account. In fact, the joint use of equity and subordinated debt prices can provide information on magnitude of expected bankruptcy costs. Knowing the magnitude of expected bankruptcy costs is necessary for calculating variables underlying policy objectives. In particular, it is illustrated that the value of expected liability of a deposit insurer would be underestimated if the bankruptcy costs were not taken into account.     

A fuzzy random periodic review system with variable lead-time and negative exponential crashing cost

In the present model a fuzzy random periodic review system has been investigated with the annual demand assumed to be a discrete fuzzy random variable with associated imprecise probabilities. Keeping in mind the widespread application of the Just-In-Time manufacturing philosophy and lead-time management being one of its most effective methods of implementation, the lead-time has been assumed to be an added control parameter. Also as it may not be always possible to resolve the lead-time into all its components and estimate their individual crashing costs, the crashing cost has been introduced as a negative exponential function of the lead-time. A methodology has been developed in this regard such that the total inventory cost is minimized and the optimal period of review, the optimal target inventory level and the optimal lead-time are determined in the process. An algorithm has been provided to encapsulate the methodology and it has been illustrated by way of a numerical example.