Paradox in a Non-Linear Capacitated Transportation Problem
We consider the parallel approximability of two problems arising from high multiplicity scheduling, namely the unweighted model with variable processing requirements and the weighted model with identical processing requirements. These two problems are known to be modelled by a class of quadratic programs that are efficiently solvable in polynomial time. On the parallel setting, both problems are P-complete and hence cannot be efficiently solved in parallel unless P = NC. To deal with the parallel...
We consider the parallel approximability of two problems arising from high multiplicity scheduling, namely the unweighted model with variable processing requirements and the weighted model with identical processing requirements. These two problems are known to be modelled by a class of quadratic programs that are efficiently solvable in polynomial time. On the parallel setting, both problems are P-complete and hence cannot be efficiently solved in parallel unless P = NC. To deal with the parallel...
This paper is concerned with scheduling when the data are not fully known before the execution. In that case computing a complete schedule off-line with estimated data may lead to poor performances. Some flexibility must be added to the scheduling process. We propose to start from a partial schedule and to postpone the complete scheduling until execution, thus introducing what we call a stabilization scheme. This is applied to the m machine problem with communication delays: in our model an estimation...
This paper is concerned with scheduling when the data are not fully known before the execution. In that case computing a complete schedule off-line with estimated data may lead to poor performances. Some flexibility must be added to the scheduling process. We propose to start from a partial schedule and to postpone the complete scheduling until execution, thus introducing what we call a stabilization scheme. This is applied to the m machine problem with communication delays: in our model an estimation...
We propose a parallel algorithm which uses both Monte-Carlo and quasi-Monte-Carlo methods. A detailed analysis of this algorithm, followed by examples, shows that the estimator's efficiency is a linear function of the processor number. As a concrete application example, we evaluate performance measures of a multi-class queueing network in steady state.
We are concerned with a class of queueing systems with controlled service rates, in which the waiting times are only observed when they take zero value. Applying a suitable filtering process, we show the existence of optimal control policies under a discounted optimality criterion.
Given a metric space we consider a general class of functionals which measure the cost of a path in joining two given points and , providing abstract existence results for optimal paths. The results are then applied to the case when is aWasserstein space of probabilities on a given set and the cost of a path depends on the value of classical functionals over measures. Conditions for linking arbitrary extremal measures and by means of finite cost paths are given.
This paper analyses an M/G/1 retrial queue with working vacation and constant retrial policy. As soon as the system becomes empty, the server begins a working vacation. The server works with different service rates rather than completely stopping service during a vacation. We construct the mathematical model and derive the steady-state queue distribution of number of customer in the retrial group. The effects of various performance measures are derived.
We deal with a logistic problem motivated by a case study from a company dealing with inland transportation of piece goods in regular cycles. The problem consists in transportation of goods among regional centres – hubs of a network. Demands on transportation are contained in a matrix of flows of goods between pairs of hubs. The transport is performed by vehicles covering the shipping demands and the task is to design a cyclical route and to place a depot for each vehicle. The route depot can be...