A tri-level optimization model for inventory control with uncertain demand and lead time

We propose an inventory control model for an uncapacitated warehouse in a manufacturing facility under demand and lead time uncertainty. The objective is to make ordering decisions to minimize the total system cost. We introduce a two-stage tri-level optimization model with a rolling horizon to address the uncertain demand and lead time regardless of their underlying distributions. In addition, an exact algorithm is designed to solve the model. We compare this model in a case study with three decision-making strategies: optimistic, moderate, and pessimistic. Our computational results suggest that the performances of these models are either consistently inferior or highly sensitive to cost parameters (such as holding cost and shortage cost), whereas the new tri-level optimization model almost always results in the lowest total cost in all parameter settings

Potential competition for biomass between biopower and biofuel under RPS and RFS2

Driven by Renewable Portfolio Standards and Renewable Fuel Standard, biopower generation and biofuel production will increasingly compete for the same biomass resource over the next two decades. We use a linear programming model to study this competition as well as other interactions between the two policies. Our model describes the U.S. renewable energy portfolio by explicitly accounting for all major renewable energy resources, unique resource availability and policy requirements in all 50 states and Washington, DC, and policy deadlines set by all RPS and RFS2 policies within a 2013-2035 modeling horizon. Our modeling results were used to address five important questions regarding interactions between RPS and RFS2 and the impact on U.S. renewable energy portfolio

A Market Analysis on Green Production Lines Penetrating into Original Equipment Manufacturers (OEMs)

Fierce market competition has been big obstacle in the growth process of sustainable/green production industry. Sustainable production lines often come into play by penetrating into traditional Original Equipment Manufacturers (OEMs). This is due to the high setup cost and opportunity risks. In this study, we look into the scenario when traditional Original Equipment Manufacturers (OEMs) introduce green production lines into their production systems. We want to address the questions whether and how the green production lines can survive in the market competitions. Analyses are conducted between ordinary and green production sectors which produce a similar type of product with different materials and techniques. A game theoretic model is formulated to analyze the competition in the market. Sensitivity analyses and numerical examples can provide suggestions to assist policy makers, government, company executives and consumers to make better and rational decisions

An Oligopoly Model to Analyze the Market and Social Welfare for Green Manufacturing Industry

As public concerns on sustainable economic development increase, an increasing number of manufactured products have found their environmentally preferable alternatives. In this study, we propose an oligopoly game theoretical model to analyze the competition between the green and ordinary manufacturing sectors. We identify cost efficiency and innovative design as key elements to the survival of green products. We also find that the effectiveness of Pigouvian tax and subsidy policies depend on product characteristics, market structures, as well as targeted results. Our small empirical examples on Corolla vs. Prius and Incandescent lamp vs. Compact fluorescent lamp (CFL) show that our modeling results are more optimistic than real market statistics. We identify pre-equilibrium market dynamics, consumer bias towards green products, and modeling limitations as the main reasons for such differences. We also investigate the market competition and total societal welfare in the presence of tax and subsidy policy intervention. The study results not only provide guidelines and managerial insights for green producers to understand the underlying factors that determine the competitiveness of green products in the market but also benefit policy makers by quantitatively showing the effectiveness of tax and subsidy policies in promoting green products

An Optimization Approach To Assessing the Self-Sustainability Potential of Food Demand in the Midwestern United States

Conventional agriculture faces significant challenges as world population grows, food demand increases, and mobility becomes increasingly constrained. Reducing the distance food needs to travel is an important goal of sustainability and resiliency, particularly in the context of a variety of transportation challenges. In this study, we developed a linear programming optimization method to assess the potential of regions to meet dietary requirements with more localized and diversified agricultural systems. Emphasis is on minimizing the distance between population centers and available cropland, accounting for variations in yield among 40 of the most marketable food crops that can be grown in the Midwestern United States. We also derived two new metrics to guide strategic planning toward more localized systems: the per capita cropland requirement and the regional self-sustainability index. Overall, we conclude that the eight-state study region would require an average of 0.49 acres (0.2 ha) per consumer with an average absolute deviation of 0.09 acres (.04 ha). The self-sustainability index is estimated at 9.3, which indicates that the region has 9.3 times the cropland needed to become self-sustaining. Targeted dietary recommendations could potentially be met within a population-weighted average distance of 13.6 miles (21.9 km)

Localizing Food Production and Purchasing for Schools

Participants will be able to compare dietary requirements and consumption of school-aged children with respect to local food production capabilities in one state/region

Magnetic Evolution and Temperature Variation in a Coronal Hole

We have explored the magnetic flux evolution and temperature variation in a coronal-hole region, using Big Bear Solar Observatory (BBSO) deep magnetograms and {\it SOHO}/EIT images observed from 2005 October 10 to 14. For comparison, we also investigated a neighboring quiet region of the Sun. The coronal hole evolved from its mature stage to its disappearance during the observing period. We have obtained the following results: (1) When the coronal hole was well developed on October 10, about 60 % of the magnetic flux was positive. The EUV brightness was 420 counts pixel$^{-1}$, and the coronal temperature, estimated from the line ratio of the EIT 195 {\AA} and 171 {\AA} images, was 1.07 MK. (2) On October 14, when the coronal hole had almost disappeared, 51 % of the magnetic flux was positive, the EUV radiance was 530 counts pixel$^{-1}$, and the temperature was 1.10 MK. (3) In the neighboring quiet region, the fraction of positive flux varied between 0.49 and 0.47. The EUV brightness displayed an irregular variation, with a mean value of 870 counts pixel$^{-1}$. The temperature was almost constant at 1.11 MK during the five-day observation. Our results demonstrate that in a coronal hole less imbalance of the magnetic flux in opposite polarities leads to stronger EUV brightness and higher coronal temperatures