Robust optimization in simulation: Taguchi and response surface methodology

Optimization of simulated systems is tackled by many methods, but most methods assume known environments. This article, however, develops a `robust' methodology for uncertain environments. This methodology uses Taguchi's view of the uncertain world, but replaces his statistical techniques by Response Surface Methodology (RSM). George Box originated RSM, and Douglas Montgomery recently extended RSM to robust optimization of real (non-simulated) systems. We combine Taguchi's view with RSM for simulated systems. We illustrate the resulting methodology through classic Economic Order Quantity (EOQ) inventory models, which demonstrate that robust optimization may require order quantities that differ from the classic EOQ

Robust Optimization in Simulation: Taguchi and Response Surface Methodology

Optimization of simulated systems is tackled by many methods, but most methods assume known environments. This article, however, develops a 'robust' methodology for uncertain environments. This methodology uses Taguchi's view of the uncertain world, but replaces his statistical techniques by Response Surface Methodology (RSM). George Box originated RSM, and Douglas Montgomery recently extended RSM to robust optimization of real (non-simulated) systems. We combine Taguchi's view with RSM for simulated systems, and apply the resulting methodology to classic Economic Order Quantity (EOQ) inventory models. Our results demonstrate that in general robust optimization requires order quantities that differ from the classic EOQ.Pareto frontier;bootstrap;Latin hypercube sampling

Robust Optimization in Simulation:Taguchi and Krige Combined

Optimization of simulated systems is the goal of many methods, but most methods as- sume known environments. We, however, develop a `robust' methodology that accounts for uncertain environments. Our methodology uses Taguchi's view of the uncertain world, but replaces his statistical techniques by Kriging. We illustrate the resulting methodology through classic Economic Order Quantity (EOQ) inventory models. Our results suggest that robust optimization requires order quantities that dier from the classic EOQ. We also compare our latest results with our previous results that do not use Kriging but Response Surface Methodology (RSM).

The More the Merrier? The Effect of Family Composition on Children's Education

Among the perceived inputs in the production' of child quality is family size; there is an extensive theoretical literature that postulates a tradeoff between child quantity and quality within a family. However, there is little causal evidence that speaks to this theory. Our analysis is able to overcome many limitations of the previous literature by using a rich dataset that contains information on the entire population of Norway over an extended period of time and allows us to match adult children to their parents and siblings. In addition, we use exogenous variation in family size induced by the birth of twins to isolate causation. Like most previous studies, we find a negative correlation between family size and children's educational attainment. However, when we include indicators for birth order, the effect of family size becomes negligible. This finding is robust to the use of twin births as an instrument for family size. In addition, we find that birth order has a significant and large effect on children's education; children born later in the family obtain less education. These findings suggest the need to revisit economic models of fertility and child production', focusing not only on differences across families but differences within families as well.

The impact of price policy on demand for alcohol in rural India

Whether raising the price of addictive goods can reduce its burden is widely debated in many countries, largely due to lack of appropriate data and robust methods. Three key concerns frequently raised in the literature are: unobserved heterogeneity; omitted variables; identification problem. Addressing these concerns, using robust instrument and employing unique individual-level panel data from Indian Punjab, this paper investigates two related propositions (i) will increase in alcohol price reduce its burden (ii) since greater incomes raise the costs of inebriation, will higher incomes affect consumption of alcohol negatively. Distinct from previous studies, the key variable of interest is the budget share of alcohol that allows studying the burden of alcohol consumption on drinker's and also on other family members. Results presented show that an increase in alcohol price is likely to be regressive, especially on the bottom quartile, with a rise in the budget share of alcohol given budget constraint. This outcome is robust to different econometric specifications. Preliminary explorations suggest that higher per capita income increases the odds of quitting drinking. Results reported have wider implications for the effective design of addiction related health policies

Sustainable Inventory Management Model for High-Volume Material with Limited Storage Space under Stochastic Demand and Supply

Inventory management and control has become an important management function, which is vital in ensuring the efficiency and profitability of a company’s operations. Hence, several research studies attempted to develop models to be used to minimise the quantities of excess inventory, in order to reduce their associated costs without compromising both operational efficiency and customers’ needs. The Economic Order Quantity (EOQ) model is one of the most used of these models; however, this model has a number of limiting assumptions, which led to the development of a number of extensions for this model to increase its applicability to the modern-day business environment. Therefore, in this research study, a sustainable inventory management model is developed based on the EOQ concept to optimise the ordering and storage of large-volume inventory, which deteriorates over time, with limited storage space, such as steel, under stochastic demand, supply and backorders. Two control systems were developed and tested in this research study in order to select the most robust system: an open-loop system, based on direct control through which five different time series for each stochastic variable were generated, before an attempt to optimise the average profit was conducted; and a closed-loop system, which uses a neural network, depicting the different business and economic conditions associated with the steel manufacturing industry, to generate the optimal control parameters for each week across the entire planning horizon. A sensitivity analysis proved that the closed-loop neural network control system was more accurate in depicting real-life business conditions, and more robust in optimising the inventory management process for a large-volume, deteriorating item. Moreover, due to its advantages over other techniques, a meta-heuristic Particle Swarm Optimisation (PSO) algorithm was used to solve this model. This model is implemented throughout the research in the case of a steel manufacturing factory under different operational and extreme economic scenarios. As a result of the case study, the developed model proved its robustness and accuracy in managing the inventory of such a unique industry

Robust Quantitative Comparative Statics for a Multimarket Paradox

We introduce a quantitative approach to comparative statics that allows to bound the maximum effect of an exogenous parameter change on a system's equilibrium. The motivation for this approach is a well known paradox in multimarket Cournot competition, where a positive price shock on a monopoly market may actually reduce the monopolist's profit. We use our approach to quantify for the first time the worst case profit reduction for multimarket oligopolies exposed to arbitrary positive price shocks. For markets with affine price functions and firms with convex cost technologies, we show that the relative profit loss of any firm is at most 25% no matter how many firms compete in the oligopoly. We further investigate the impact of positive price shocks on total profit of all firms as well as on social welfare. We find tight bounds also for these measures showing that total profit and social welfare decreases by at most 25% and 16.6%, respectively. Finally, we show that in our model, mixed, correlated and coarse correlated equilibria are essentially unique, thus, all our bounds apply to these game solutions as well.Comment: 23 pages, 1 figur

Environmental public good provision under robust decision making

We study public good provision in a two-country dynamic setup with environmental externalities. In this framework, we examine robust decision making under potential misspecification of the process that describes the evolution of the environmental public good. Robust policies, arising from fear of model misspecification, help to correct for the inefficiencies associated with free riding and thus increase the provision of the public good. As a result, there can be welfare gains from robust policies even when the fear of model misspecification proves to be unfounded

Does parental education affect fertility? Evidence from pre-demographic transition Prussia

While  women’s  employment  opportunities,  relative  wages,  and  the child quantity‐quality trade‐off have been studied as factors underlying  historical fertility limitation, the role of parental education  has received little attention.  We  combine  Prussian  county  data  from  three censuses—1816,  1849,  and  1867—to  estimate  the relationship between women’s education and their  fertility before the demographic transition.  Despite  controlling  for  several  demand  and  supply  factors,  we  find  a  negative  residual  effect  of  women’s  education  on  fertility.  Instrumental‐variable estimates, using exogenous variation in women's  education  driven  by  differences in  landownership  inequality,  suggest  that the effect of women’s education on fertility is causal.