A mixed 0–1 nonlinear optimization model and algorithmic approach for the collision avoidance in ATM: Velocity changes through a time horizon

2012 ◽  
Vol 39 (12) ◽  
pp. 3136-3146 ◽  
Author(s):  
Antonio Alonso-Ayuso ◽  
Laureano F. Escudero ◽  
F. Javier Martín-Campo
DYNA ◽  
2019 ◽  
Vol 86 (209) ◽  
pp. 255-260 ◽  
Author(s):  
Julian Andres Zapata-cortes ◽  
Martin Dario Arango-Serna ◽  
Frank Alexander Ballesteros Riveros ◽  
Wilson Adarme - Jaimes

The storage allocation in warehouse is about of deciding the corresponding areas in which the products must be allocated. It can be made using different techniques to stablish the specific position for the products. Some applications provide solutions and evaluate results independently, allowing the identification of its potential in warehouses. This paper presents the application of a storage allocation model in a food company considering several products in a defined time horizon. The algorithm identifies the operation area and the corresponding spaces that are required for the products allocation, aimed to reduce holding and material handling costs. As a result, the application of the algorithm produces a complete product allocation in each period and improves the cost efficiency in the warehouse.


2020 ◽  
Vol 68 (12) ◽  
pp. 985-1000
Author(s):  
Marius Roland ◽  
Martin Schmidt

AbstractWe present a mixed-integer nonlinear optimization model for computing the optimal expansion of an existing tree-shaped district heating network given a number of potential new consumers. To this end, we state a stationary and nonlinear model of all hydraulic and thermal effects in the pipeline network as well as nonlinear models for consumers and the network’s depot. For the former, we consider the Euler momentum and the thermal energy equation. The thermal aspects are especially challenging. Here, we develop a novel polynomial approximation that we use in the optimization model. The expansion decisions are modeled by binary variables for which we derive additional valid inequalities that greatly help to solve the highly challenging problem. Finally, we present a case study in which we identify three major aspects that strongly influence investment decisions: the estimated average power demand of potentially new consumers, the distance between the existing network and the new consumers, and thermal losses in the network.


2021 ◽  
pp. 1-13
Author(s):  
Sahana Upadhya ◽  
Michael J. Wagner

Abstract A recent increase in the integration of renewable energy systems in existing power grids along with a lack of integrated dispatch models has led to waste in power produced. This paper presents a mixed-integer nonlinear optimization model for hybrid renewable-generator-plus-battery systems, with the objective of maximizing long-term profit. Prior studies have revealed that both high and low state of charge (SOC) of the battery is detrimental to its lifetime and results in reduced battery capacity over time. In addition, increased number of cycles of charge and discharge also causes capacity reduction. This paper models these two factors with a constraint relating capacity loss to the SOC and number of cycles completed by the battery. Loss in capacity is penalized in the objective function of the optimization model, thereby disincentivizing high and low SOCs and frequent cycling. A rolling time horizon optimization approach is used to overcome the computational difficulties of achieving global optimality within a long-term time horizon. By incorporating battery degradation, the model is capable of maximizing the profits from the power dispatch to the grid while also maximizing the life of the battery. This paper exercises the model within a case study using a sample photovoltaic system generation time series that considers multiple battery capacities. The results indicate that the optimal battery lifetime is extended in comparison to conventional models that ignore battery degradation in dispatch decisions. Finally, we analyze the relationship between battery operational decisions and the resultant capacity fade.


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