1,721,032 research outputs found
Fairness Issues in Congestion Pricing with Different Classes of Customers
No full textDip. di Matematica p. e a., Università di Padov
Equitable Demand Management Strategies for Different Classes of Customers
No full textThis paper deals with the problem of finding equitable demand
management strategies in congested systems with the presence of several classes
of customers. Although the conclusions of the paper can be easily adapted to
any market-based demand management philosophy, we mainly focus on congestion
pricing, starting from a purely market-based economic approach.
In this approach, the congestion toll paid by a customer should be set equal
to the external cost he imposes on other customers. When demand consists of
customers belonging to different classes, application of this principle may lead
to tolls that are unaffordable for customers of one or more of these classes. This
raises important issues of fairness.
In this paper we discuss several alternative approaches where considerations
of equitability and affordability are incorporated into the process of assessing
congestion prices. An application to the determination of the appropriate
landing fees at a congested airport serves as an illustration of the proposed
approaches
Influence of electron-beam parameters on the radiation-induced formation of graphitic onions
No full textIt is shown that to form spherical graphitic onions by intense electron bombardment of graphitized carbon inside the electron microscope, irradiation must be performed at energies above the threshold of elastic atomic displacement, and at beam current densities higher than about 150 A cm(-2). Under these strong non-equilibrium conditions, it is possible to obtain the dynamic stability of the spherical shells, which appear fundamentally unstable in absence of irradiation
An Aggregate Stochastic Programming Model for Air Traffic Flow Management
No full textIn this paper, we present an aggregate mathematical model for air traffic flow management (ATFM), a
problem of great concern both in Europe and in the United States. The model extends previous
approaches by simultaneously taking into account three important issues: (i) the model explicitly incorporates
uncertainty in the airport capacities; (ii) it also considers the trade-off between airport arrivals
and departures, which is a crucial issue in any hub airport; and (iii) it takes into account the interactions
between different hubs.
The level of aggregation proposed for the mathematical model allows us to solve realistic size instances
with a commercial solver on a PC. Moreover it allows us to compute solutions which are perfectly consistent
with the Collaborative Decision-Making (CDM) procedure in ATFM, widely adopted in the USA and
which is currently receiving a lot of attention in Europe. In fact, the proposed model suggests the number
of flights that should be delayed, a decision that belongs to the ATFM Authority, rather than assigning
delays to individual aircraft
A GRASP metaheuristic for microarray data analysis
No full textThe Weighted Gene Regulatory Network (WGRN) problem consists in pruning a regulatory network obtained from DNA microarray gene expression data, in order to identify a reduced set of candidate elements which can explain the expression of all other genes. Since the problem appears to be particularly hard for general-purpose solvers, we develop a Greedy Randomized Adaptive Search Procedure (GRASP) and refine it with three alternative Path Relinking procedures. For comparison purposes, we also develop a Tabu Search algorithm with a self-adapting tabu tenure. The experimental results show that GRASP performs better than Tabu Search and that Path Relinking significantly contributes to its effectiveness
An integer optimization approach for reverse engineering of gene regulatory networks
No full textGene regulatory networks are a common tool to describe the chemical interactions between genes in a living cell. This paper considers the Weighted Gene Regulatory Network (WGRN) problem, which consists in identifying a reduced set of interesting candidate regulatory elements which can explain the expression of all other genes. We provide an integer programming formulation based on a graph model and derive from it a branch-and-bound algorithm which exploits the Lagrangian relaxation of suitable constraints. This allows to determine lower bounds tighter than CPLEX on most benchmark instances, with the exception of the sparser ones. In order to determine feasible solutions for the problem, which appears to be a hard task for general-purpose solvers, we also develop and compare two metaheuristic approaches, namely a Tabu Search and a Variable Neighborhood Search algorithm. The experiments performed on both of them suggest that diversification is a key feature to solve the problem
A Markov Decision Model for the 2-Period Probabilistic TSP
No full textDIP. DI MATEMATICA P. E A., UNIVERSITA` DI PADOV
Multimode extensions of combinatorial optimization problems
Full text linkWe review some complexity results and present a viable heuristic approach based on the Variable Neighborhood Search (VNS) framework for multimode extension of combinatorial optimization problems, such as the the Set Covering Problem (SCP) and the Covering Location Problem (CLP)
A Multi-period TSP with Stochastic Regular and Urgent Demands
No full textIn this paper, we study the multi-period TSP problem with stochastic urgent and regular demands. Urgent demands
have to be satisfied immediately while regular demands can be satisfied either immediately or the day after. Demands
appear stochastically at nodes. The objective is to minimize the average long-run delivery costs, knowing the probabilities
governing the demands at nodes.
The problem is cast as a Markov Process with Costs and, at least in principle, can be solved using an approach originally
proposed by Howard [R.A. Howard, Dynamic Programming and Markov Processes, MIT, Cambridge, USA, 1960]
for Markov Processes with Rewards. However, the number of states of the Markov Process grows exponentially with the
number of nodes in the network which pose a limit on the dimension of the instances that are computationally tractable.
We suggest a second Markov approach considering a system (Aggregate Model) whose number of states grows only polynomially
with the number of nodes in the network. The important relations between the optimal solutions of the original
and the aggregate models will be discussed. Finally, we also propose a hybrid procedure which combines both models. The
viability of the proposed methodology is shown by applying the procedure to a numerical example
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