Minimization of Extended Quadratic Functions.
Minimization of nonsmooth convex functionals in Banach spaces.
Minimizing and maximizing a linear objective function under a fuzzy relational equation and an inequality constraint
This paper provides an extension of results connected with the problem of the optimization of a linear objective function subject to fuzzy relational equations and an inequality constraint, where is an operation. This research is important because the knowledge and the algorithms presented in the paper can be used in various optimization processes. Previous articles describe an important problem of minimizing a linear objective function under a fuzzy relational equation and an inequality constraint,...
Minimizing convex functions by continuous descent methods.
Minimizing costs can be costly.
Minimizing energy use for a road expansion in a transportation system using optimal control theory.
Minimizing risk probability for infinite discounted piecewise deterministic Markov decision processes
The purpose of this paper is to study the risk probability problem for infinite horizon piecewise deterministic Markov decision processes (PDMDPs) with varying discount factors and unbounded transition rates. Different from the usual expected total rewards, we aim to minimize the risk probability that the total rewards do not exceed a given target value. Under the condition of the controlled state process being non-explosive is slightly weaker than the corresponding ones in the previous literature,...
Minimizing the earliness and tardiness cost of a sequence of tasks on a single machine
Assume that tasks must be processed by one machine in a fixed sequence. The processing time, the preferred starting time and the earliness and tardiness costs per time unit are known for each task. The problem is to allocate each task a starting time such that the total cost incurred by the early and tardy tasks is minimum. Garey et al. have proposed a nice algorithm for the special case of symmetric and task-independent costs. In this paper we first extend that algorithm to the case of asymmetric...
Minimizing the Earliness and Tardiness Cost of a Sequence of Tasks on a Single Machine
Assume that n tasks must be processed by one machine in a fixed sequence. The processing time, the preferred starting time and the earliness and tardiness costs per time unit are known for each task. The problem is to allocate each task a starting time such that the total cost incurred by the early and tardy tasks is minimum. Garey et al. have proposed a nice O(nlogn) algorithm for the special case of symmetric and task-independent costs. In this paper we first extend that algorithm to the...
Minimizing the fuel consumption of a vehicle from the Shell Eco-marathon: a numerical study
We apply four different methods to study an intrinsically bang-bang optimal control problem. We study first a relaxed problem that we solve with a naive nonlinear programming approach. Since these preliminary results reveal singular arcs, we then use Pontryagin’s Minimum Principle and apply multiple indirect shooting methods combined with homotopy approach to obtain an accurate solution of the relaxed problem. Finally, in order to recover a purely bang-bang solution for the original problem, we...
Minimizing the number of tardy jobs for the single machine scheduling problem: MIP-based lower and upper bounds
This paper considers the problem of scheduling n jobs on a single machine. A fixed processing time and an execution interval are associated with each job. Preemption is not allowed. The objective is to find a feasible job sequence that minimizes the number of tardy jobs. On the basis of an original mathematical integer programming formulation, this paper shows how good-quality lower and upper bounds can be computed. Numerical experiments are provided for assessing the proposed approach.
Minimizing total weighted completion time on single machine with past-sequence-dependent setup times and exponential time-dependent and position-dependent learning effects.
Minimum convex-cost tension problems on series-parallel graphs
We present briefly some results we obtained with known methods to solve minimum cost tension problems, comparing their performance on non-specific graphs and on series-parallel graphs. These graphs are shown to be of interest to approximate many tension problems, like synchronization in hypermedia documents. We propose a new aggregation method to solve the minimum convex piecewise linear cost tension problem on series-parallel graphs in operations.
Minimum convex-cost tension problems on series-parallel graphs
We present briefly some results we obtained with known methods to solve minimum cost tension problems, comparing their performance on non-specific graphs and on series-parallel graphs. These graphs are shown to be of interest to approximate many tension problems, like synchronization in hypermedia documents. We propose a new aggregation method to solve the minimum convex piecewise linear cost tension problem on series-parallel graphs in O(m3) operations.
Minimum cut in directed planar networks
Min-max pour des critères multiples
Minmax regret combinatorial optimization problems: an Algorithmic Perspective
Uncertainty in optimization is not a new ingredient. Diverse models considering uncertainty have been developed over the last 40 years. In our paper we essentially discuss a particular uncertainty model associated with combinatorial optimization problems, developed in the 90's and broadly studied in the past years. This approach named minmax regret (in particular our emphasis is on the robust deviation criteria) is different from the classical approach for handling uncertainty, stochastic approach,...
Minmax regret combinatorial optimization problems: an Algorithmic Perspective
Uncertainty in optimization is not a new ingredient. Diverse models considering uncertainty have been developed over the last 40 years. In our paper we essentially discuss a particular uncertainty model associated with combinatorial optimization problems, developed in the 90's and broadly studied in the past years. This approach named minmax regret (in particular our emphasis is on the robust deviation criteria) is different from the classical approach for handling uncertainty, stochastic approach,...
MIP-based heuristics for multi-item capacitated lot-sizing problem with setup times and shortage costs
We address a multi-item capacitated lot-sizing problem with setup times that arises in real-world production planning contexts. Demand cannot be backlogged, but can be totally or partially lost. Safety stock is an objective to reach rather than an industrial constraint to respect. The problem is NP-hard. We propose mixed integer programming heuristics based on a planning horizon decomposition strategy to find a feasible solution. The planning horizon is partitioned into several sub-horizons over...
Mise à jour de la métrique dans les méthodes de quasi-Newton réduites en optimisation avec contraintes d'égalité