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Predicting optimal solution cost with conditional probabilities

Levi H. S. Lelis, Roni Stern, Ariel Felner, Sandra Zilles, Robert C. Holte
2014 Annals of Mathematics and Artificial Intelligence  
In this paper we propose an algorithm, named Solution Cost Predictor (SCP), that accurately and efficiently predicts the optimal solution cost of a problem instance without finding the actual solution.  ...  They find the optimal solution cost as a side effect. However, there are applications in which all one wants to know is an estimate of the optimal solution cost.  ...  This process is repeated Fig. 1 The first step of a CDP prediction for start state s 0 Predicting optimal solution cost with conditional probabilities for all types at the second level of prediction.  ... 
doi:10.1007/s10472-014-9432-8 fatcat:uu5gjkqdjjfjrlrmkbo5wb5jkm

Machinery Condition Monitoring System Selection A Multi-Objective Decision Approach Using GA

A.K. Verma, A. Srividya, P.G. Ramesh
2008 2008 First International Conference on Emerging Trends in Engineering and Technology  
The trade offs between the Pareto optimal solutions of various objectives have been studied and the effects of variation of the maintenance objective function values with detectability and predictability  ...  The issues which are critical to CBM, namely, predictability, detectability as well as implications of availability and cost have been considered in the framework to provide effective decision support.  ...  Likewise, Figure 4 shows the variation of cost with unavailability. Figure 5 gives the relation between the ratio of probabilities CM/PM and unavailability.  ... 
doi:10.1109/icetet.2008.127 dblp:conf/icetet/VermaSR08 fatcat:ccgh2oxh6vgxbdrjet4h7uofum

Integration of stochastic deterioration models with multicriteria decision theory for optimizing maintenance of bridge decks

George Morcous, Zoubir Lounis
2006 Canadian journal of civil engineering (Print)  
The stochastic deterioration model is based on the first-order Markov chain that predicts the probabilistic time-variation of the condition of bridge decks.  ...  The multi-objective optimization model takes into account two important and conflicting criteria: the minimization of maintenance costs, and the maximization of the network condition.  ...  Markov-chains are used as performance prediction models for bridge components by defining discrete condition states and accumulating the probability of transition from one condition state to another over  ... 
doi:10.1139/l06-011 fatcat:zbjand64dngfdkogdnak5fpicq

Bridge Management Strategy Based on Extreme User Costs for Bridge Network Condition

Ladislaus Lwambuka, Primus V. Mtenga
2014 Advances in Civil Engineering  
of bridge deck condition, and minimization of traffic disruption and associated user costs.  ...  This paper deals with the second scenario of traffic closure in the absence of alternative diversion routes which in essence results in extreme user cost.  ...  This analysis leads to the establishment of transition probabilities which can be used to predict future bridge conditions [7] .  ... 
doi:10.1155/2014/390359 fatcat:kbtavsturvbszo5d6tiwi3vtqm

Optimum analysis of pavement maintenance using multi-objective genetic algorithms

Amr A. Elhadidy, Emad E. Elbeltagi, Mohammad A. Ammar
2015 HBRC Journal  
From the optimal solutions represented by cost and condition, a decision maker can easily obtain the information of the maintenance and rehabilitation planning with minimum action costs and maximum condition  ...  A two-objective optimization model considers minimum action costs and maximum condition for used road network.  ...  The optimal solutions of this twoobjective optimization model provide the decision makers with the maintenance and rehabilitation planning with maximum condition and minimum action costs.  ... 
doi:10.1016/j.hbrcj.2014.02.008 fatcat:mobcow6vyfhg3kn4qc3fypkpr4

A Multiobjective and Stochastic System for Building Maintenance Management

Z. Lounis, D. J. Vanier
2000 Computer-Aided Civil and Infrastructure Engineering  
prediction models with a multiobjective optimization approach.  ...  optimal allocation of funds and prioritization of roofs for maintenance, repair and replacement that simultaneously satisfy the following conflicting objectives: (i) minimization of maintenance and repair costs  ...  and predict the future condition or performance.  ... 
doi:10.1111/0885-9507.00196 fatcat:4mg67rmktbh2nllgkom4rhe45q

Maintenance optimization of infrastructure networks using genetic algorithms

G. Morcous, Z. Lounis
2005 Automation in Construction  
Optimal maintenance alternatives are those solutions that minimize the life-cycle cost of an infrastructure network while fulfilling reliability and functionality requirements over a given planning horizon  ...  process, maintenance operations, and initial condition, as well as their practicality for network level analysis.  ...  René Gagnon, Bridge Engineer, of the Structures Department-Ministére des Transports du Québec-for their invaluable help in providing the authors with all available data, manuals and other needed information  ... 
doi:10.1016/j.autcon.2004.08.014 fatcat:wahbgpblobcyxgmwsr2xgqimqu

Care Strategies for Reducing Hospital Readmissions Using Stochastic Programming

Behshad Lahijanian, Michelle Alvarado
2021 Healthcare  
The stochastic programming model has probabilistic constraints to control the expected readmission probability for a set of patients.  ...  We develop a multi-condition care strategy model to help hospitals prioritize treatment plans and allocate resources.  ...  Predictive Approaches Predictive approaches aim to estimate the probability of readmission.  ... 
doi:10.3390/healthcare9080940 fatcat:5k6kxxgx5nhivawttf7c5rioye

An overview of inference methods in probabilistic classifier chains for multilabel classification

Deiner Mena, Elena Montañés, José Ramón Quevedo, Juan José del Coz
2016 Wiley Interdisciplinary Reviews Data Mining and Knowledge Discovery  
cost, both in terms of solutions explored and execution time.  ...  Only −approximate algorithm with = .0 theoretically guarantees reaching an optimal solution in terms of subset 0/1 loss.  ...  This means that it always predicts the label combination with the highest joint conditional probability.  ... 
doi:10.1002/widm.1185 fatcat:wf2hoo5zcrcbvptoktyl2tno54

A Second Order Stochastic Network Equilibrium Model, II: Solution Method and Numerical Experiments

David Watling
2002 Transportation Science  
It is seen that a quasi-periodic behaviour commonly arises in the SP model, with the predictions radically different from the GSUE(2) model.  ...  applicable to the realistic case of probit-based choice probabilities.  ...  Given mean predicted link travel costs y , which induce route costs y T  , the q k drivers on each movement choose between the alternative routes independently and with common probabilities 5.  ... 
doi:10.1287/trsc. fatcat:7alllvjklzdizfmduwifysnurq


Ankang Ji, Xiaolong Xue, Yuna Wang, Xiaowei Luo, Minggong Zhang
2020 Journal of Civil Engineering and Management  
For case 2, the largest annual maintenance cost in the first year is $15.16 million with four types of maintenance activities.  ...  Thus, this research presents an integrated approach based on the Markov chain and Particle swarm optimization algorithm which aims to consider the predicted pavement condition and optimize the pavement  ...  with the maintenance horizon after predicting the future pavement conditions by MC.  ... 
doi:10.3846/jcem.2020.13751 fatcat:rtovwp52ynek7jp4hnji6ssdii

A Node Scheduling Game based on Water Cycle Algorithm for Energy Efficient Wireless Sensor Networks

M. Karthiga, R. Venkatesan
2017 International Journal of Computer Applications  
Again the energy efficiency of the solution is proved by the simulation results. General Terms Energy Efficient Algorithm  ...  Sensor Networks are expected to sustain for a long period of time with limited battery power. Among the many approaches used, Node Scheduling is effective in increasing the Network Lifetime.  ...  The improved performance of NSG with time is explained by the increase in accuracy of Conditional Probability.  ... 
doi:10.5120/ijca2017913742 fatcat:kxhejnk6pbhzta65acc56js4ma

Pavement maintenance optimization model using Markov Decision Processes

P Mandiartha, C F Duffield, I S b M Razelan, A b H Ismail
2017 Journal of Physics, Conference Series  
programming solution.  ...  These unique characteristics include a direct inclusion of constraints into the formulation of MDP, the use of an average cost method of MDP, and the policy development process based on the dual linear  ...  MDP solutions The solutions for MDP can be classified into two types which are an average cost method and a discounted cost method [1] .  ... 
doi:10.1088/1742-6596/890/1/012104 fatcat:32j5knj7unerlkqbffekscsqom

A performance-based Pavement Management System for the road network of Montreal city—a conceptual framework [chapter]

Md Amin, Luis Amador-Jiménez
2014 Asphalt Pavements  
Other important objectives (e.g. mobility, safety, accessibility and social cost), along with investments to upgrade and expand the network, are normally left outside the modeling.  ...  A performance-based pavement management system can predict the response and performance of pavement under actual dynamic traffic loads.  ...  Moreover, the vehicle, accident and time costs are directly associated with pavement condition deterioration.  ... 
doi:10.1201/b17219-36 fatcat:op5csuhkrvcs3fmqynciub564m

HVAC Scheduling under Data Uncertainties: A Distributionally Robust Approach [article]

Guanyu Tian, Qun Zhou, Samy Faddel, Wenyi Wang
2021 arXiv   pre-print
The numerical results indicate that the costs of the proposed DRO method are up to 6.6% lower compared with conventional techniques of optimization under uncertainties.  ...  This paper first studies deterministic optimization, robust optimization, and stochastic optimization to minimize the daily operation cost with constraints of indoor air temperature comfort and mechanic  ...  The cost of DRO solutions with ε ∈ (0, 2.5] is bounded by the cost of DRO-0 and DRO-2.5.  ... 
arXiv:2103.05850v1 fatcat:gzpbjkuv4zgepkmvecrxoithhi
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