Commitment and Dispatch of Heat and Power Units via Affinely Adjustable Robust Optimization

The joint management of heat and power systems is believed to be key to the integration of renewables into energy systems with a large penetration of district heating. Determining the day-ahead unit commitment and production schedules for these systems is an optimization problem subject to uncertainty stemming from the unpredictability of demand and prices for heat and electricity. Furthermore, owing to the dynamic features of production and heat storage units as well as to the length and granularity of the optimization horizon (e.g., one whole day with hourly resolution), this problem is in essence a multi-stage one. We propose a formulation based on robust optimization where recourse decisions are approximated as linear or piecewise-linear functions of the uncertain parameters. This approach allows for a rigorous modeling of the uncertainty in multi-stage decision-making without compromising computational tractability. We perform an extensive numerical study based on data from the Copenhagen area in Denmark, which highlights important features of the proposed model. Firstly, we illustrate commitment and dispatch choices that increase conservativeness in the robust optimization approach. Secondly, we appraise the gain obtained by switching from linear to piecewise-linear decision rules within robust optimization. Furthermore, we give directions for selecting the parameters defining the uncertainty set (size, budget) and assess the resulting trade-off between average profit and conservativeness of the solution. Finally, we perform a thorough comparison with competing models based on deterministic optimization and stochastic programming.Comment: 31 page

Coproducción: Una revisión de la literatura

[ES] El objetivo del presente artículo es analizar la literatura existente en el entorno de la coproducción. De acuerdo con Deuermeyer y Pierskalla (1978), es posible afirmar que existe coproducción cuando un proceso productivo da como resultado más de un producto de manera simultánea. La coproducción aparece en ambientes de alta y baja tecnología de producción. La coproducción, suele ocurrir en entornos de producción en los que algunos procesos no se conocen/comprenden perfectamente y/o no están totalmente bajo control (coproducción incontrolada). Sin embargo, tal y como, se ha podido constatar en la realidad industrial, en ocasiones el proceso de coproducción, si se conoce/comprende perfectamente (coproducción controlada). La coproducción puede ser un fenómeno intrínseco al propio proceso productivo (coproducción no deliberada). Aunque en ocasiones puede ser escogida por el gestor del proceso (coproducción deliberada). Así, resulta interesante clasificar la literatura respecto a estas variables, pues hasta la fecha no se había realizado, proporcionando al lector una visión clara de la literatura existente en torno a la coproducción.Este trabajo ha sido realizado gracias a la financiación del Ministerio de Ciencia e Innovación a través del proyecto CORSARI MAGIC: Coordinación de operaciones en redes de suministro/demanda ajustadas, resilientes a la incertidumbre: modelos y algoritmos para la gestión de la incertidumbre y la complejidad, DPI: 2010-18243.Vidal Carreras, PI. (2011). Coproducción: Una revisión de la literatura. Working Papers on Operations Management. 2(1):11-17. doi:10.4995/wpom.v2i1.810SWORD111721BITRAN, G. B., & LEONG, T.-Y. (1995). Co-production of substitutable products. Production Planning & Control, 6(1), 13-25. doi:10.1080/09537289508930249Bitran, G. R., & Dasu, S. (1992). Ordering Policies in an environment of Stochastic Yields and Substitutable Demands. Operations Research, 40(5), 999-1017. doi:10.1287/opre.40.5.999Bitran, G. R., & Gilbert, S. M. (1994). Co-Production Processes with Random Yields in the Semiconductor Industry. Operations Research, 42(3), 476-491. doi:10.1287/opre.42.3.476Bitran, G. R., & Leong, T.-Y. (1992). Deterministic Approximations to Co-Production Problems with Service Constraints and Random Yields. Management Science, 38(5), 724-742. doi:10.1287/mnsc.38.5.724Bitran, G. R., & Yanasse, H. H. (1984). Deterministic Approximations to Stochastic Production Problems. Operations Research, 32(5), 999-1018. doi:10.1287/opre.32.5.999Bravo, D., Rodríguez, E., & Medina, M. (2009). Nisin and lacticin 481 coproduction by Lactococcus lactis strains isolated from raw ewes’ milk. Journal of Dairy Science, 92(10), 4805-4811. doi:10.3168/jds.2009-2237Deuermeyer, B. L. (1979). A Multi-Type Production System for Perishable Inventories. Operations Research, 27(5), 935-943. doi:10.1287/opre.27.5.935Deuermeyer, B. L., & Pierskalla, W. P. (1978). A By-Product Production System with an Alternative. Management Science, 24(13), 1373-1383. doi:10.1287/mnsc.24.13.1373DUENYAS, I., & TSAI, C.-Y. (2000). Control of a manufacturing system with random product yield and downward substitutability. IIE Transactions, 32(9), 785-795. doi:10.1080/07408170008967438Evans, R. V. (1969). Inventory control of by-products. Naval Research Logistics Quarterly, 16(1), 85-92. doi:10.1002/nav.3800160107Garcia-Sabater, J. P.; Vidal-Carreras, P. I. (2010). Programación de producción en los proveedores del automóvil. Revista Virtual Pro, Vol. 104, p. 23.García-Sabater, J. P., Vidal-Carreras, P.I., & García-Sabater, J. J. (2005). Estudio de la Problemática de Programación de la Producción en el sector del Automóvil. Aplicación a una red de fabricación, in VIII Congreso de Ingeniería de Organización.Gerchak, Y., & Grosfeld-Nir, A. (1999). International Journal of Flexible Manufacturing Systems, 11(4), 371-377. doi:10.1023/a:1008131213614GERCHAK, Y., TRIPATHY, A., & WANG, K. (1996). Co-production models with random functionality yields. IIE Transactions, 28(5), 391-403. doi:10.1080/07408179608966286Grosfeld-Nir, A., & Gerchak, Y. (2004). Multiple Lotsizing in Production to Order with Random Yields: Review of Recent Advances. Annals of Operations Research, 126(1-4), 43-69. doi:10.1023/b:anor.0000012275.01260.f5LISBONA, P., & ROMEO, L. (2008). Enhanced coal gasification heated by unmixed combustion integrated with an hybrid system of SOFC/GT. International Journal of Hydrogen Energy, 33(20), 5755-5764. doi:10.1016/j.ijhydene.2008.06.031Mcgillivray, R., & Silver, E. (1978). Some Concepts For Inventory Control Under Substitutable Demand*. INFOR: Information Systems and Operational Research, 16(1), 47-63. doi:10.1080/03155986.1978.11731687Nahmias, S., & Moinzadeh, K. (1997). Lot Sizing with Randomly Graded Yields. Operations Research, 45(6), 974-989. doi:10.1287/opre.45.6.974Nielsen, D. R., Yoon, S.-H., Yuan, C. J., & Prather, K. L. J. (2010). Metabolic engineering of acetoin and meso-2, 3-butanediol biosynthesis in E. coli. Biotechnology Journal, 5(3), 274-284. doi:10.1002/biot.200900279Öner, S., & Bilgiç, T. (2008). Economic lot scheduling with uncontrolled co-production. European Journal of Operational Research, 188(3), 793-810. doi:10.1016/j.ejor.2007.05.016Ou, J., & Wein, L. M. (1995). Dynamic Scheduling of a Production/Inventory System with By-Products and Random Yield. Management Science, 41(6), 1000-1017. doi:10.1287/mnsc.41.6.1000Caner Taşkın, Z., & Tamer Ünal, A. (2009). Tactical level planning in float glass manufacturing with co-production, random yields and substitutable products. European Journal of Operational Research, 199(1), 252-261. doi:10.1016/j.ejor.2008.11.024Tomlin, B., & Wang, Y. (2008). Pricing and Operational Recourse in Coproduction Systems. Management Science, 54(3), 522-537. doi:10.1287/mnsc.1070.0807Vidal-Carreras, P. I., & Garcia-Sabater, J. P. (2009). Comparison of heuristics for an economic lot scheduling problem with deliberated coproduction. Journal of Industrial Engineering and Management, 2(3). doi:10.3926/jiem.2009.v2n3.p437-463Yano, C. A., & Lee, H. L. (1995). Lot Sizing with Random Yields: A Review. Operations Research, 43(2), 311-334. doi:10.1287/opre.43.2.31

Urban sustainable development and the challenge of French metropolitan strategies. GSPE Working Paper 11/04/2008

This article focuses on some salient issues of urban sustainable development in France, specifically with regard to six urban agglomerations: Bordeaux, Lille, Lyon, Montpellier, Nantes and Toulouse. The reticular dimension of these issues is analysed with reference to the ways a plurality of actors imagine, project and realise the construction of cities, rather than through sectoral points of view. This relational approach is divided according to a triple focus in which we successively address: firstly, the state of SD policies in the listed major French cities, in terms of contents and conception; secondly, their implementation from the perspective of instruments; and finally, the circuits of their realisation. Thus, urban SD appears within a (locally variable) set of linkages that place these issues firmly in areas of interrelations and intersections

Rules and Values in Virtual Optimization of California Hydropower

Optimization models for California’s hydropower system are designed to be decision-support tools and aids for climate adaptation decision-making. In practice, they fall short of this goal. One potential explanation is that optimization models are not more successful because they are built on, and depend on, a misrepresentation of law and politics. The legal reality of California’s hydropower system is a web of networked jurisdictions of multiple federal and state agencies, with varying levels of coordination, long periods of legally obligated stability with rigid rules, and prone to conflict, but with multiple procedures for conflict resolution. Barriers to climate adaptation from that mix vary according to where a given dam is located. The virtual institutional arrangements represented in optimization models are not a simplification of existing arrangements. Instead, they are a dramatic replacement. That replacement is deliberate and reasoned. As seen in two optimization models supported by the state of California, CALVIN and INFORM, the operation of the optimization function of computer models depends on a virtual system of rules that are centrally controlled, coordinated, nimble, and without the possibility of conflict (let alone conflict resolution). But that smooth virtual system comes with a real cost. Institutional economics suggests that this mismatch between existing formal law and represented law may upend the results of models, since value is determined from institutional context

Integrating Long-Term and Short-Term Contracting in Beef Supply Chains

Published version made available with the permission of INFORMS</p

Dynamic Pricing and Supply Coordination with Reimbursement Contract under Random Yield and Demand

This paper investigates the dynamic pricing and supply chain coordination in a decentralized system that consists of one supplier and one manufacturer, in which both the market demand and production yield are stochastic. We show that the centralized expected profit is jointly concave in the production quantity and order quantity when the price is ex-ante selected. We also derive the equilibrium strategies in the decentralized system and prove that the entire profit of supply chain is inevitably lower than that under centralized system. Based on this, we propose a reimbursement contract to coordinate the decentralized supply chain so as to achieve the maximized profit. It is worth mentioning that, under reimbursement contract, the equilibrium production and order quantities are irrelevant to the manufacturer's risk sharing coefficient but are only determined by the supplier’s risk sharing coefficient

How Yield Process Misspecification Affects the Solution of Disassemble-to-order Problems

Random yields from production are often present in manufacturing systems and there are several ways that this can be modeled. In disassembly planning, the yield uncertainty in harvesting parts from cores can be modeled as either stochastically proportional or binomial, two of these alternatives. A statistical analysis of data from engine remanufacturing of a major car producer fails to provide conclusive evidence on which kind of yield randomness might prevail. In order to gain insight into the importance of this yield assumption, the impact of possible yield misspecification on the solution of the disassemble-to-order problem is investigated. Our results show that the penalty for misspecifying the yield method can be substantial, and provide insight on when the penalty would likely be problematic. The results also indicate that in the absence of conclusive information on which alternative should be chosen, presuming binomial yields generally leads to lower cost penalties and therefore preferable results

Dynamic Pricing and Replenishment with Customer Upgrades

We study a joint implementation of price‐ and availability‐based product substitution to better match demand and constrained supply across vertically differentiated products. Our study is motivated by firms that utilize dynamic pricing as well as customer upgrades, as ex ante and ex post mechanisms, respectively, to mitigate inventory mismatches. To gain insight into how offering product upgrades impacts optimal price selection, we formulate a multiple period, nested two‐stage model where the firm first sets prices and replenishment levels for each product while the demand is still uncertain, and after observing the demand, decides how many (if any) of the customers to upgrade to a higher quality product. We characterize the structure of the optimal upgrade, pricing and replenishment policies and find that firms having greater flexibility to offer product upgrades can restrain their reliance on dynamic pricing, enabling them to better protect the price differentiation between the products. We also show how the quality differential between the products or changes in the replenishment cost structures influence the optimal policy. Using insights gained from the optimal policy structure, we construct a heuristic policy and find that it performs well across various parameter values. Finally, we consider an extension in which the firm dynamically sets upgrade fees in each period. Our results overall help further our understanding of the intricate relationship among a firm's decisions on pricing, replenishment, and product upgrades in an effort to better match demand and constrained supply

Essays on Operational Flexibilities in Production Planning under Supply and Quality Uncertainty

This dissertation investigates the use of operational flexibilities in production planning in order to mitigate the negative effects of supply and quality uncertainty. Uncertainties in supply and quality are commonly experienced among agro-businesses, and in particular, in the wine industry. The goal of the dissertation is to provide prescriptive solutions in mitigating such risks from the lives of agricultural businesses. The first essay of the dissertation examines the impact of supply and quality uncertainty on the investment decisions made by winemakers who lease vineyard space to grow their own fruit. At the end of the growing season, the winemaker receives an uncertain amount of high- and low-quality grapes, due to varying growing conditions such as adverse weather conditions, diseases and natural disasters. High-quality grapes are used in the making of a high-end (reserve) wine, and low-quality grapes are used for the production of a low-end wine. In this study, we investigate the benefits of the downward substitution flexibility, where the winemaker uses its excess high-quality grapes for the production of its low-end wine. In addition, we examine the influence of, and the interrelationships between, three forms of operational flexibilities: downward substitution, price-setting, and fruit trading flexibilities. The second essay of the dissertation investigates the use of advance selling to mitigate quality risk in wine production. This essay examines the influence of quality uncertainty on winemakers\u27 decisions regarding the allocation of its wine for retail operations. Specifically, we study what proportion of the wine should be sold through regular distribution channels versus what proportion should be sold as wine futures in advance of bottling. Due to the intricacies of the production method, the quality of wine may vary from the moment aging begins in the barrel to the time it is bottled and sold to the general public. This study examines the use of wine futures, whereby a winemaker sells its wine while it is still in the barrel in order to reduce the quality rating risk at the time of distribution. Overall, wine futures not only allow the winemaker to pass on the quality rating risk established through expert tastings to consumers but also let them bring in cash for immediate reinvestment into the next vintage