Cake eating, exhaustible resource extraction, life-cycle saving, and non-atomic games: Existence theorems for a class of optimal allocation problems

2009 ◽  
Vol 33 (6) ◽  
pp. 1345-1360 ◽  
Author(s):  
Siu Fai Leung
2018 ◽  
Vol 336 ◽  
pp. 394-407 ◽  
Author(s):  
Ka Chun Cheung ◽  
Jan Dhaene ◽  
Yian Rong ◽  
Sheung Chi Phillip Yam

Author(s):  
Minh Y Nguyen ◽  
Pham Dieu Thuy

Abstract This paper presents a new architecture of energy hubs for animal farms considering the availability of energy resources in the farm such as biogas, solar, etc. It is proposed to combine three energy carriers: biogas, heat and electricity into an aggregate system to improve the energy efficiency of the farm. The problem is to determine the optimal allocation of distributed energy resources such as biogas generators, photovoltaics, battery and electric grid, etc. with the objective function is minimizing the total cost of energy hubs, i. e. life cycle cost while subjected to the constraint of heat, electricity and gas demands. The uncertainty of renewable energy is taken into account not only with the daily and monthly variation of the resource but the forecasting error as well. In addition, the sensitivity of the life cycle cost with respect to the price of electricity is analysed in different scenarios. The problem is examined in a case study of a typical pig farm in Northern Vietnam in both cases: with and without the ability to sell the surplus electricity to the grid. The simulation result shows the effectiveness of the proposed energy hub compared to other approaches.


1966 ◽  
Vol 3 (3) ◽  
pp. 261-268 ◽  
Author(s):  
Paul E. Green ◽  
Michael H. Halbert ◽  
Patrick J. Robinson

This article is concerned with the effect of a problem's environmental context on the learning of an “optimal” allocation rule. A series of sales allocation problems were presented to groups of executive and student subjects. While the allocation principle remained invariant over conditions, the context of the problem was experimentally modified. Results of the experiments indicated that: (1) both groups of subjects performed about the same; (2) the modifications made in the “surface” complexity of the problem did not markedly affect the probability of learning the allocation principle; and (3) a constant-probability-over-trials model appeared to describe learning behavior.


1999 ◽  
Vol 65 (2) ◽  
pp. 227-237 ◽  
Author(s):  
Tryggvi Thor Herbertsson ◽  
Gylfi Zoega
Keyword(s):  

2009 ◽  
Vol 27 (2) ◽  
pp. 270-296 ◽  
Author(s):  
Miguel Martinez ◽  
Sylvain Rubenthaler ◽  
Etienne Tanré

2011 ◽  
Vol 133 (8) ◽  
Author(s):  
Ching-Shin Norman Shiau ◽  
Jeremy J. Michalek

We pose a reformulated model for optimal design and allocation of conventional (CV), hybrid electric (HEV), and plug-in hybrid electric (PHEV) vehicles to obtain global solutions that minimize life cycle greenhouse gas (GHG) emissions of the fleet. The reformulation is a twice-differentiable, factorable, nonconvex mixed-integer nonlinear programming (MINLP) model that can be solved globally using a convexification-based branch-and-reduce algorithm. We compare results to a randomized multistart local-search approach for the original formulation and find that local-search algorithms locate global solutions in 59% of trials for the two-segment case and 18% of trials for the three-segment case. The results indicate that minimum GHG emissions are achieved with a mix of PHEVs sized for 25–45 miles of electric travel. Larger battery packs allow longer travel on electrical energy, but production and weight of underutilized batteries result in higher GHG emissions. Under the current average U.S. grid mix, PHEVs offer a nearly 50% reduction in life cycle GHG emissions relative to equivalent conventional vehicles and about 5% improvement over HEVs when driven on the standard urban driving cycle. Optimal allocation of different PHEVs to different drivers turns out to be of second order importance for minimizing net life cycle GHGs.


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