Solving Electric Market Quadratic Problems by Branch and Fix Coordination Methods

The electric market regulation in Spain (MIBEL) establishes the rules for bilateral and futures contracts in the day-ahead optimal bid problem. Our model allows a price-taker generation company to decide the unit commitment of the thermal units, the economic dispatch of the bilateral and futures contracts between the thermal units and the optimal sale bids for the thermal units observing the MIBEL regulation. The uncertainty of the spot prices is represented through scenario sets. We solve this model on the framework of the Branch and Fix Coordination metodology as a quadratic two-stage stochastic problem. In order to gain computational efficiency, we use scenario clusters and propose to use perspective cuts. Numerical results are reportedPeer Reviewe

A Parallelizable Heuristic for Solving the Generic Materials and Operations Planning in a Supply Chain Network: A Case Study from the Automotive Industry

[EN] A trend in up-to date developments in multi-site operations planning models is to consider in details the different ways to produce, buy or transport products and the distributed decision-making process for operations planning. One of the most generic approaches to support global optimization in those supply chain networks by considering all the different operations alternatives and product structures is the Generic Materials & Operations Planning Problem. This problem can be modelled by a Mixed Integer Linear Programming model capable of considering production, transportation, procurement tasks and their alternatives and other relevant issues such as packaging. The aim of this paper is to introduce the implementation of a parallelizable heuristic method for materials and operations planning and its application to a case of a Supply Chain Network of the automotive industry. The approach uses variants of the GMOP model to overcome traditional MRP systems' limitations.Maheut ., JP.; García Sabater, JP. (2013). A Parallelizable Heuristic for Solving the Generic Materials and Operations Planning in a Supply Chain Network: A Case Study from the Automotive Industry. IFIP Advances in Information and Communication Technology. 397:151-157. doi:10.1007/978-3-642-40352-1_20S151157397Maheut, J., Garcia-Sabater, J.P.: La Matriz de Operaciones y Materiales y la Matriz de Operaciones y Recursos, un nuevo enfoque para resolver el problema GMOP basado en el concepto del Stroke. Dirección y Organización 45, 46–57 (2011)Garcia-Sabater, J.P., Maheut, J., Marin-Garcia, J.A.: A new formulation technique to model Materials and Operations Planning: the Generic Materials and Operations Planning (GMOP) Problem. European J. Industrial Engineering 7, 119–147 (2013)Mula, J., Maheut, J., Garcia-Sabater, J.P.: Supply Chain Network Design. Journal of Marketing and Operations Management Research 1, 378–383 (2012)Dudek, G., Stadtler, H.: Negotiation-based collaborative planning between supply chains partners. European Journal of Operational Research 163, 668–687 (2005)Torabi, S.A., Hassini, E.: Multi-site production planning integrating procurement and distribution plans in multi-echelon supply chains: an interactive fuzzy goal programming approach. International Journal of Production Research 47, 5475–5499 (2009)Kanyalkar, A.P., Adil, G.K.: Aggregate and detailed production planning integrating procurement and distribution plans in a multi-site environment. International Journal of Production Research 45, 5329–5353 (2007)de Kok, T.G., Fransoo, J.C.: Planning Supply Chain Operations: Definition and Comparison of Planning Concepts. In: Graves, S.C. (ed.) Handbooks in Operations Research and Management Science Supply Chain Management: Design, Coordination and Operation, vol. 11, pp. 597–675. Elsevier (2003)Buschkühl, L., Sahling, F., Helber, S., Tempelmeier, H.: Dynamic capacitated lot-sizing problems: a classification and review of solution approaches. OR Spectrum (2009)Maheut, J., Garcia-Sabater, J.P., Mula, J.: A supply Chain Operations Lot-Sizing and Scheduling Model with Alternative Operations. In: Sethi, S.P., Bogataj, M., Ros-McDonnell, L. (eds.) Proceedings of the Industrial Engineering: Innovative Networks, 5th International Conference on Industrial Engineering and Industrial Management "CIO 2011", Cartagena, Spain, pp. 309–316. Springer, London (2012)Garcia-Sabater, J.P., Maheut, J., Garcia-Sabater, J.J.: A two-stage sequential planning scheme for integrated operations planning and scheduling system using MILP: the case of an engine assembler. Flexible Services and Manufacturing Journal 24, 171–209 (2012)Pinto, J.M., Chen, P., Papageorgiou, L.G.: A discrete/continuous time MILP model for medium term planning of single stage multiproduct plants, pp. 1–6. Elsevier, B.V. (2007)Scheer, A.W.: Business Process Engineering - Reference Models for Industrial Enterprises. Springer (1994)Lin, J.T., Chen, T.L., Lin, Y.T.: Critical material planning for TFT-LCD production industry. International Journal of Production Economics 122, 639–655 (2009)Escudero, L.F.: CMIT, capacitated multi-level implosion tool. European Journal of Operational Research 76, 511–528 (1994)Maheut, J., Garcia-Sabater, J.P., Valero-Herrero, M.: MILP model for solving the supply chain operations scheduling problem with alternative operations considering delay penalization: a case study of a mass customization company. In: Proceedings of the 41st International Conference on Computers & Industrial Engineering, pp. 289–294 (2011

The Impact of Perceived Expectations and Uncertainty on Firm Investment

This paper analyses the (differential) impact of perceived expectations and uncertainty on investment spending in small and large firms. We analyse two types of investment, viz. aggregate investment and investment in energy-saving technologies, using Dutch firm level data. The results show that expectations and uncertainty about input- and output prices and domestic demand have substantial but different effects on investment spending in firms of different sizes. Furthermore, we find evidence, at least for small firms, that there are important differences between the effects of uncertainty about input and output variable

Design and construction of the MicroBooNE detector

This paper describes the design and construction of the MicroBooNE liquid argon time projection chamber and associated systems. MicroBooNE is the first phase of the Short Baseline Neutrino program, located at Fermilab, and will utilize the capabilities of liquid argon detectors to examine a rich assortment of physics topics. In this document details of design specifications, assembly procedures, and acceptance tests are reported

Designing Rapid Transit Networks from the Results of a Survey

In this work we present a two-stage approach for designing rapid transit networks. It is based on another approach that we described elsewhere. In the first stage, the stations and links to be constructed are selected by solving an integer linear programming model that maximizes an estimation of the number of trips through the rapid transit network. In the second stage, a set of lines is generated by utilizing a greedy heuristic procedure that, taking into consideration the transfers that should be made by the users to arrive at their destinations, attempts to maximize a more accurate estimation for the number of trips. This new estimation is done by means of a modification of the well-known Floyd-Warshall algorithm. The main contributions are a novel way of computing the expected number of trips by making use of the results from a survey amongst the potential users of the rapid transit network, as well as the contemplation of the possibility of linking certain pairs of station locations by more than one line. Some computational experiments on several randomly generated instances are also reported

On due-date based valid cuts for the sequential ordering problem

Integer Programming, Lagrangean relaxation, Hamiltonian Path, Valid Cuts, Tightening, 90C10, 90C27, 90C30,

A note for tightening 0–1 models

Tighter formulations, Covers, Cliques, Equivalency, Redundancy, 90C10, 90C05,