Pure parsimony haplotyping (PPH) problem is important in bioinformatics because rational haplotyping inference plays important roles in analysis of genetic data, mapping complex genetic diseases such as Alzheimer'...
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Pure parsimony haplotyping (PPH) problem is important in bioinformatics because rational haplotyping inference plays important roles in analysis of genetic data, mapping complex genetic diseases such as Alzheimer's disease, heart disorders and etc. Haplotypes and genotypes are m-length sequences. Although several integerprograming models have already been presented for PPH problem, its NP-hardness characteristic resulted in ineffectiveness of those models facing the real instances especially instances with many heterozygous sites. In this paper, we assign a corresponding number to each haplotype and genotype and based on those numbers, we set a mixed integer programing model. Using numbers, instead of sequences, would lead to less complexity of the new model in comparison with previous models in a way that there are neither constraints nor variables corresponding to heterozygous nucleotide sites in it. Experimental results approve the efficiency of the new model in producing better solution in comparison to two state-of-the art haplotyping approaches. (C) 2016 Elsevier Inc. All rights reserved.
A two-stage load control scheme is presented to address severe under-frequency conditions. The first stage is event-based under-frequency load shedding that guarantees fast response to the detected high-consequence di...
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A two-stage load control scheme is presented to address severe under-frequency conditions. The first stage is event-based under-frequency load shedding that guarantees fast response to the detected high-consequence disturbances, for initial system protection. The control signals are obtained by solving mixed-integer programming problems. After the first stage, model predictive control is triggered in the second stage for step-by-step online closed-loop control of interruptible loads, the amount of which is identified via solving linear programming problems. Trajectory sensitivities are used in the optimization problems in both stages to facilitate the analysis. The proposed scheme has been tested on a 9-bus system and on the New England 39-bus system.
Swofford and Whitney (1987, 1988, 1994) investigated the validity of two key assumptions underlying representative agent models of macroeconomics. These assumptions are utility maximization and weak separability. Usin...
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Swofford and Whitney (1987, 1988, 1994) investigated the validity of two key assumptions underlying representative agent models of macroeconomics. These assumptions are utility maximization and weak separability. Usingmixedinteger programming, we check revealed preference conditions for these assumptions. We find that M1, money defined by Friedman and Schwartz (1963), and a broad aggregate are weakly separable. We find that consumption goods and leisure and nondurables and services are weakly separable. We find that M2, M3, and MZM are not weakly separable. Finally, we find three categories of consumption, durables, nondurables and services, do not form an aggregate.
In this paper, a multi-echelon location-distribution problem is modeled considering customer priorities. A lexicographic approach is implemented to determine the most preferred distribution path according to the prior...
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In this paper, a multi-echelon location-distribution problem is modeled considering customer priorities. A lexicographic approach is implemented to determine the most preferred distribution path according to the priorities of customers. The predetermined number of trucks moving from depots and satellites is considered in the proposed model. The results show that the proposed approach can better consider the customers with different priorities, while more important customers will have low total costs compared to the classical approach. Moreover, the sensitivity analysis has been done for discovering the effects of related parameters in the model. (C) 2016 Sharif University of Technology. All rights reserved.
One of the main challenges for widespread penetration of plug-in hybrid electric vehicles (PHEVs) is their impact on the electricity grid. The energy sector must anticipate and prepare for this extra demand and implem...
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One of the main challenges for widespread penetration of plug-in hybrid electric vehicles (PHEVs) is their impact on the electricity grid. The energy sector must anticipate and prepare for this extra demand and implement long-term planning for electricity production. In this paper, the additional electricity demand on the Ontario electricity grid from charging PHEVs is incorporated into an electricity production planning model. A case study pertaining to Ontario energy planning is considered to optimize the value of the cost of the electricity over sixteen years (2014-2030). The objective function consists of the fuel costs, fixed and variable operating and maintenance costs, capital costs for new power plants, and the retrofit costs of existing power plants. Five different case studies are performed with different PHEVs penetration rates, types of new power plants, and CO2 emission constraints. Among all the cases studied, the one requiring the most new capacity, (similar to 8748 MW), is assuming the base case with 6% reduction in CO2 in year 2018 and high PHEV penetration. The next highest one is the base case, plus considering doubled NG prices, PHEV medium penetration rate and no CO2 emissions reduction target with an increase of 34.78% in the total installed capacity in 2030. Furthermore, optimization results indicate that by not utilizing coal power stations the CO2 emissions are the lowest: similar to 500 tonnes compared to similar to 900 tonnes when coal is permitted.
The Operating Theater (OT) is known to be a fluctuating production system. The unpredictability of populations' needs has an impact on the required human and material resources. This makes the Operating Theater a ...
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ISBN:
(纸本)9782960053265
The Operating Theater (OT) is known to be a fluctuating production system. The unpredictability of populations' needs has an impact on the required human and material resources. This makes the Operating Theater a dynamic environment. Thus, use of dynamic models is getting more realistic to solve OT layout problems. The Dynamic Operating Theater Layout Problem (DOTLP) has a main objective, to minimize the interdepartmental travel costs among facilities and to minimize the rearrangement costs, by studying an individual layout for each distinctive period based on patients demand, subject to a set of constraints of distances, available areas, and non-overlapping facilities according to international medical standards and specifications. In this paper, we propose a mixedinteger linear programming (MILP) model for solving DOTLP. For this, we generate a set of data to determine the optimal positions as well as the orientations of facilities on several illustrative multi-section Operating Theater cases.
We propose a hybrid method integrating agent-based modeling and heuristic tree search to solve complex batch scheduling problems. Agent-based modeling describes the batch process and constructs a feasible schedule und...
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We propose a hybrid method integrating agent-based modeling and heuristic tree search to solve complex batch scheduling problems. Agent-based modeling describes the batch process and constructs a feasible schedule under various constraints. To overcome myopic decisions of agents, the agent-based simulation is embedded into a heuristic search algorithm. The heuristic algorithm partially explores the solution space generated by the agent-based simulation. Because global information of the objective function value is used in the search algorithm, the schedule performance is improved. The proposed method shares the advantages from both agent-based modeling and mixed integer programing, achieving a better balance between the solution efficiency and the schedule performance. As a polynomial-time algorithm, the hybrid method is applicable to large-scale complex industrial scheduling problems. Its performance is demonstrated by comparing with agent-based modeling and mixed integer programing in two case studies, including a complex one from The Dow Chemical Company. (C) 2013 Elsevier Ltd. All rights reserved.
Facility Layout Problem (FLP) has been widely used in industrial systems to manage the space and the facilities within the floor space. The layout has a great impact on the productivity and the efficiency of running a...
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ISBN:
(纸本)9782960053241
Facility Layout Problem (FLP) has been widely used in industrial systems to manage the space and the facilities within the floor space. The layout has a great impact on the productivity and the efficiency of running an organization. In health care systems, FLP is applied to hospital layout in a way to improve the health process, but the Operating Theater layout has received less attention instead of its importance. Existing research dealing with the OT Layout were based on graph theoretic methods, which ignore the size, the orientation and the shape of rooms and just focused on the desirable adjacency objective. This paper proposes a mixedinteger Linear Programming (MILP) formulation for the Operating Theater Layout problem. The formulation uses a multi-goal approach to optimize two objectives: the first quantitative objective minimizes the interdepartmental traveling costs, whereas the second qualitative objective maximizes the closeness of the facilities. The presented model determines the position and orientation of each activity according to the OT international standards. The applicability of the model is demonstrated on four illustrative examples using commercial optimization software.
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