A hybrid projection-proximal point algorithm.
A local and global search combine particle swarm optimization algorithm for job-shop scheduling to minimize makespan.
A Metaheuristic Approach to Solving the Generalized Vertex Cover Problem
AMS Subj. Classification: 90C27, 05C85, 90C59The topic is related to solving the generalized vertex cover problem (GVCP) by genetic algorithm. The problem is NP-hard as a generalization of well-known vertex cover problem which was one of the first problems shown to be NP-hard. The definition of the GVCP and basics of genetic algorithms are described. Details of genetic algorithm and numerical results are presented in [8]. Genetic algorithm obtained high quality solutions in a short period of time.
A model for a dynamic preventive maintenance policy.
A multi-destination daily carpooling problem and an ant colony based resolution method
The rising car usage deriving from growth in jobs and residential population causes air pollution, energy waste and consumption of people’s time. Public transport cannot be the only answer to this increasing transport demand. Carpooling, which is based on the idea that sets of car owners pick up colleagues while driving to or from the workplace, has emerged to be a viable possibility for reducing private car usage in congested areas. Its actual practice requires a suitable information system support...
A multivariable multiobjective predictive controller
Predictive control of MIMO processes is a challenging problem which requires the specification of a large number of tuning parameters (the prediction horizon, the control horizon and the cost weighting factor). In this context, the present paper compares two strategies to design a supervisor of the Multivariable Generalized Predictive Controller (MGPC), based on multiobjective optimization. Thus, the purpose of this work is the automatic adjustment of the MGPC synthesis by simultaneously minimizing...
A new algorithm for optimal solution of fixed charge transportation problem
Fixed charge transportation problem (FCTP) is a supply chain problem. In this problem, in addition to the cost per unit for each transported product, a fixed cost is also required. The aim is to carry out the transportation process at the lowest possible cost. As with all supply chain problems, this problem may have one, two, or three stages. An algorithm that can find the optimal solution for the problem in polynomial time is not known, even if it is a single-stage problem. For this reason, new...
A new evolutionary algorithm for multiobjective optimization based on endocrine paradigm.
A new evolutionary optimization technique.
A New Genetic Representation for Quadratic Assignment Problem
A new heuristic for the quadratic assignment problem.
A new modeling and solution approach for the number partitioning problem.
A Note on Spanning Trees for Network Location Problems
A note on the hardness results for the labeled perfect matching problems in bipartite graphs
In this note, we strengthen the inapproximation bound of O(logn) for the labeled perfect matching problem established in J. Monnot, The Labeled perfect matching in bipartite graphs, Information Processing Letters96 (2005) 81–88, using a self improving operation in some hard instances. It is interesting to note that this self improving operation does not work for all instances. Moreover, based on this approach we deduce that the problem does not admit constant approximation algorithms for connected...
A novel fuzzy c-regression model algorithm using a new error measure and particle swarm optimization
This paper presents a new algorithm for fuzzy c-regression model clustering. The proposed methodology is based on adding a second regularization term in the objective function of a Fuzzy C-Regression Model (FCRM) clustering algorithm in order to take into account noisy data. In addition, a new error measure is used in the objective function of the FCRM algorithm, replacing the one used in this type of algorithm. Then, particle swarm optimization is employed to finally tune parameters of the obtained...
A perturbation approach to approximate value iteration for average cost Markov decision processes with Borel spaces and bounded costs
The present paper studies the approximate value iteration (AVI) algorithm for the average cost criterion with bounded costs and Borel spaces. It is shown the convergence of the algorithm and provided a performance bound assuming that the model satisfies a standard continuity-compactness assumption and a uniform ergodicity condition. This is done for the class of approximation procedures that can be represented by linear positive operators which give exact representation of constant functions and...
A polarized adaptive schedule generation scheme for the resource-constrained project scheduling problem
This paper presents a hybrid schedule generation scheme for solving the resource-constrained project scheduling problem. The scheme, which is called the Polarized Adaptive Scheduling Scheme (PASS), can operate in a spectrum between two poles, namely the parallel and serial schedule generation schemes. A polarizer parameter in the range between zero and one indicates how similarly the PASS behaves like each of its two poles. The presented hybrid is...
A polarized adaptive schedule generation scheme for the resource-constrained project scheduling problem
This paper presents a hybrid schedule generation scheme for solving the resource-constrained project scheduling problem. The scheme, which is called the Polarized Adaptive Scheduling Scheme (PASS), can operate in a spectrum between two poles, namely the parallel and serial schedule generation schemes. A polarizer parameter in the range between zero and one indicates how similarly the PASS behaves like each of its two poles. The presented hybrid is...
A priority rule-based heuristic for resource investment project scheduling problem with discounted cash flows and tardiness penalties.
A production-inventory model for a deteriorating item incorporating learning effect using genetic algorithm.