Maximizing and minimizing fuzzy sets.
Maximizing residual capacity in connection-oriented networks.
Maximum cardinality 1-restricted simple 2-matchings.
Maximum Entropy and Utility in a Transportation System
Maximum likelihood estimates and confidence intervals of an M/M/R/N queue with balking and heterogeneous servers
This paper considers an M/M/R/N queue with heterogeneous servers in which customers balk (do not enter) with a constant probability . We develop the maximum likelihood estimates of the parameters for the M/M/R/N queue with balking and heterogeneous servers. This is a generalization of the M/M/2 queue with heterogeneous servers (without balking), and the M/M/2/N queue with balking and heterogeneous servers in the literature. We also develop the confidence interval formula for the parameter , the...
Maximum likelihood estimates and confidence intervals of an M/M/R/N queue with balking and heterogeneous servers
This paper considers an M/M/R/N queue with heterogeneous servers in which customers balk (do not enter) with a constant probability (1 - b). We develop the maximum likelihood estimates of the parameters for the M/M/R/N queue with balking and heterogeneous servers. This is a generalization of the M/M/2 queue with heterogeneous servers (without balking), and the M/M/2/N queue with balking and heterogeneous servers in the literature. We also develop the confidence interval formula for the parameter...
Maximum likelihood estimates with order restrictions on probabilities and odds ratios: A geometric programming approach.
Max-separable equations and the set covering
Mean-variance optimality for semi-Markov decision processes under first passage criteria
This paper deals with a first passage mean-variance problem for semi-Markov decision processes in Borel spaces. The goal is to minimize the variance of a total discounted reward up to the system's first entry to some target set, where the optimization is over a class of policies with a prescribed expected first passage reward. The reward rates are assumed to be possibly unbounded, while the discount factor may vary with states of the system and controls. We first develop some suitable conditions...
Measure Theoretic Versions of Linear Programming.
Measuring and Evaluating Efficiency and Effectiveness Using Goal Programming and Data Envelopment Analysis in a Fuzzy Environment
Measuring consistency and inconsistency of pair comparison systems
In this paper we deal with mathematical modeling of real processes that are based on preference relations in the sense that, for every pair of distinct alternatives, the processes are linked to a value of preference degree of one alternative over the other one. The use of preference relations is usual in decision making, psychology, economics, knowledge acquisition techniques for knowledge-based systems, social choice and many other social sciences. For designing useful mathematical models of such...
Mechanized experiment planning in automaton-environment systems
Medical cost trajectories and onsets of cancer and noncancer diseases in US elderly population.
Medium distances of probability-fuzzy points and an application to linear programming
MEMOTS: a memetic algorithm integrating tabu search for combinatorial multiobjective optimization
We present in this paper a new multiobjective memetic algorithm scheme called MEMOX. In current multiobjective memetic algorithms, the parents used for recombination are randomly selected. We improve this approach by using a dynamic hypergrid which allows to select a parent located in a region of minimal density. The second parent selected is a solution close, in the objective space, to the first parent. A local search is then applied to the offspring. We experiment this scheme with a new multiobjective...
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Metaheuristics based on Bin Packing for the line balancing problem
The line balancing problem consits in assigning tasks to stations in order to respect precedence constraints and cycle time constraints. In this paper, the cycle time is fixed and the objective is to minimize the number of stations. We propose to use metaheuristics based on simulated annealing by exploiting the link between the line balancing problem and the bin packing problem. The principle of the method lies in the combination between a metaheuristic and a bin packing heuristic. Two representations of...
Metasearch information fusion using linear programming
For a specific query merging the returned results from multiple search engines, in the form of a metasearch aggregation, can provide significant improvement in the quality of relevant documents. This paper suggests a minimax linear programming (LP) formulation for fusion of multiple search engines results. The paper proposes a weighting method to include the importance weights of the underlying search engines. This is a two-phase approach which in the first phase a new method for computing the importance...
Metasearch information fusion using linear programming
For a specific query merging the returned results from multiple search engines, in the form of a metasearch aggregation, can provide significant improvement in the quality of relevant documents. This paper suggests a minimax linear programming (LP) formulation for fusion of multiple search engines results. The paper proposes a weighting method to include the importance weights of the underlying search engines. This is a two-phase approach which in...