Quadratic stabilization of LPV system by an LTI controller based on ILMI algorithm.
Reconfigurable Dynamic Cellular Manufacturing System: A New Bi-Objective Mathematical Model
Dynamic Cell Formation Problem (DCFP) seeks to cope with variation in part mix and demands using machine relocation, replication, and removing; whilst from practical point of view it is too hard to move machines between cells or invest on machine replication. To cope with this deficiency, this paper addresses Reconfigurable Dynamic Cell Formation Problem (RDCFP) in which machine modification is conducted instead of their relocation or replication in order to enhance machine capabilities to process...
RedInv-SA : a simulated annealing for the quadratic assignment problem
Redinv-SA: la simulated annealing for the quadratic assignment problem
An algebraic and combinatorial approach to the study of the Quadratic Assignment Problem produced theoretical results that can be applied to (meta) heuristics to give them information about the problem structure, allowing the construction of algorithms. In this paper those results were applied to inform a Simulated Annealing-type heuristic (which we called RedInv-SA). Some results from tests with known literature instances are presented.
Results of short-period helicopter system identification using output-error and hybrid search-gradient optimization algorithm.
Robust goal programming
Rounding Strategies for Mixed Integer Programs Arising from Chemical Production Planning
Scatter Search Based Metaheuristic for Robust Optimization of the Deploying Of “Dwdm” Technology on Optical Networks With Survivability
Semidefinite Programming Based Algorithms for the Sparsest Cut Problem
In this paper we analyze a known relaxation for the Sparsest Cut problem based on positive semidefinite constraints, and we present a branch and bound algorithm and heuristics based on this relaxation. The relaxed formulation and the algorithms were tested on small and moderate sized instances. It leads to values very close to the optimum solution values. The exact algorithm could obtain solutions for small and moderate sized instances, and the best heuristics obtained optimum or near optimum...
Semidefinite Programming Based Algorithms for the Sparsest Cut Problem
In this paper we analyze a known relaxation for the Sparsest Cut problem based on positive semidefinite constraints, and we present a branch and bound algorithm and heuristics based on this relaxation. The relaxed formulation and the algorithms were tested on small and moderate sized instances. It leads to values very close to the optimum solution values. The exact algorithm could obtain solutions for small and moderate sized instances, and the best heuristics obtained optimum or near optimum...
Simulated annealing algorithms and Markov chains with rare transitions
Simulated Annealing and Joint Manufacturing Batch- Sizing
Simulated Annealing and Tabu Search for Discrete-Continuous Project Scheduling with Discounted Cash Flows
Discrete-continuous project scheduling problems with positive discounted cash flows and the maximization of the NPV are considered. We deal with a class of these problems with an arbitrary number of discrete resources and one continuous, renewable resource. Activities are nonpreemptable, and the processing rate of an activity is a continuous, increasing function of the amount of the continuous resource allotted to the activity at a time. Three common payment models – Lump Sum Payment, Payments at...
Solution of a fractional combinatorial optimization problem by mixed integer programming
Fractionnal mathematical programs appear in numerous operations research, computer science and economic domains. We consider in this paper the problem of maximizing the sum of 0–1 hyperbolic ratios (SRH). In contrast to the single ratio problem, there has been little work in the literature concerning this problem. We propose two mixed-integer linear programming formulations of SRH and develop two different strategies to solve them. The first one consists in using directly a general-purpose mixed-integer...
Solving maximum independent set by asynchronous distributed hopfield-type neural networks
We propose a heuristic for solving the maximum independent set problem for a set of processors in a network with arbitrary topology. We assume an asynchronous model of computation and we use modified Hopfield neural networks to find high quality solutions. We analyze the algorithm in terms of the number of rounds necessary to find admissible solutions both in the worst case (theoretical analysis) and in the average case (experimental Analysis). We show that our heuristic is better than the...
Solving single and multiobjective models for an assembly line design problem through ant colony algorithms.
Solving the Geophysical Inversion Problem Using Genetic Algorithms
Solving the Minimum Independent Domination Set Problem in Graphs by Exact Algorithm and Greedy Heuristic
In this paper we present a new approach to solve the Minimum Independent Dominating Set problem in general graphs which is one of the hardest optimization problem. We propose a method using a clique partition of the graph, partition that can be obtained greedily. We provide conditions under which our method has a better complexity than the complexity of the previously known algorithms. Based on our theoretical method, we design in the second part of this paper an efficient algorithm by including...
Solving the simple plant location problem by genetic algorithm
The simple plant location problem (SPLP) is considered and a genetic algorithm is proposed to solve this problem. By using the developed algorithm it is possible to solve SPLP with more than 1000 facility sites and customers. Computational results are presented and compared to dual based algorithms.
Solving the simple plant location problem by genetic algorithm
The simple plant location problem (SPLP) is considered and a genetic algorithm is proposed to solve this problem. By using the developed algorithm it is possible to solve SPLP with more than 1000 facility sites and customers. Computational results are presented and compared to dual based algorithms.