In this paper the short term scheduling optimization of a combined cycle power plant is accomplished by exploiting hybrid systems, i.e. systems evolving according to continuous dynamics, discrete dynamics, and logic rules. Discrete features of a power plant are, for instance, the possibility of turning on/off the turbines, operating constraints like minimum up and down times and the different types of start up of the turbines. On the other hand, features with continuous dynamics are power and steam output, the corresponding fuel consumption, etc. The union of these properties characterize the hybrid behavior of a combined cycle power plant. In order to model both the continuous/discrete dynamics and the switching between different operating conditions we use the framework of Mixed Logic Dynamical systems. Then, we recast the economic optimization problem as a Model Predictive Control (MPC) problem, that allows us to optimize the plant operations by taking into account the time variability of both prices and electricity/steam demands. Because of the presence of integer variables, the MPC scheme is formulated as a mixed integer linear program that can be solved in an efficient way via dedicated software.

M anufacturers adopt a variety of channels for the sale of their products in the attempt to deliver the highest possible value to end consumers. For instance, a manufacturers' retail arm provides consumers with the instant gratification of product purchase and the benefit of in-store shopping assistance, whereas their online arm offers potential benefits by selling to market segments that value shopping convenience, product variety, availability, and customization. The main difference between these two channels is that consumers cannot "touch and feel" the product before they make an online purchase, whereas they can physically inspect and often even experience the product before making an in-store purchase. As a consequence, the online arm implies a higher degree of uncertainty about product fit than the retail arm. The ensuing possibility that consumers will return the product, due to product misfit, might impact the manufacturer's design of the channels of distribution. We show that product marginal value and salvage value for product returns determine whether the manufacturer will sell his product through "bricks" only, "bricks and clicks," or "clicks" only. Our work highlights the pivotal role that online and retail channels play in the manufacturers' sales strategies in a market characterized by returns, wherein the online channel reduces double price marginalization and the retail channel curtails the number of returns. In particular, we show that a "bricks and clicks" channel structure may be the most profitable option for the manufacturer, due to its flexibility in reducing returns without adhering to strict return policies that would hurt sales.

Downstream firms increasingly recognize the importance of integrating social and environmental concerns with their businesses. As a consequence, they urge to create incentives for their suppliers to invest in corporate social responsibility (CSR) activities. Contracts to provide these incentives are rarely observed in practice. If not totally absent, contracts may be incomplete, in that unforeseen contingencies or some CSR attributes that are difficult to measure may not be included in the contract. We show that incentives for CSR investments can also be provided through the supply chain structure, which consists of the distribution of ownership rights over the firms' assets of production, and involves horizontal and/or vertical alliances among supply chain members. Motivated by examples in agricultural contexts, this study adopts the property rights approach to study the impact of supply chain structures on the adoption of CSR activities. We show that the structure that best incentivizes CSR investments depends on the interaction between CSR vertical synergy, free‐riding, and countervailing power. One of the main findings is that the alliance between suppliers is beneficial only if the revenues generated by a downstream investment are sufficiently high. In fact, only in this case, the suppliers can appropriate a sufficiently large stake of the revenues generated downstream, thanks to their countervailing power. When the upstream investment costs become high, however, the suppliers will invest in CSR only if the downstream distributor is vertically integrated. The resulting structure of a cooperative will best incentivize CSR investments only if the CSR vertical synergy between the two tiers of the supply chain is sufficiently high.

Abstract. In this paper the optimization of a combined cycle power plant is accomplished by exploiting hybrid systems, i.e. systems evolving according to continuous dynamics, discrete dynamics, and logic rules. The possibility of turning on/off the gas and steam turbine, the operating constraints (minimum up and down times) and the different types of start up of the turbines characterize the hybrid behavior of a combined cycle power plant. In order to model both the continuous/discrete dynamics and the switching between different operating conditions we use the framework of Mixed Logic Dynamical systems. Next, we recast the economic optimization problem as a Model Predictive Control (MPC) problem, that allows us to optimize the plant operations by taking into account the time variability of both prices and electricity/steam demands. Because of the presence of integer variables, the MPC scheme is formulated as a mixed integer linear program that can be solved in an efficient way by using commercial solvers.

This study characterizes the class of Pareto optimal returns policies between a manufacturer and a retailer who receives consumer returns. The manufacturer may take a costly hidden action that reduces the expected number of products returned by consumers, which when realized is hidden information known only to the retailer. When faced with consumer returns, the retailer must decide whether to send the product back to the manufacturer, who harvests a low salvage value, or to engage in costly refurbishment that permits the returned product to be resold to consumers. We find that the optimal returns policies may be implemented through the payment by the manufacturer of a full refund to the retailer of the wholesale price for any returns as well as a bonus paid to the retailer that is decreasing in the number of returns to the manufacturer.