Search results for " Program"
showing 10 items of 3075 documents
MECHANISM DESIGN FOR OPTIMAL CONSENSUS PROBLEMS
2006
We consider stationary consensus protocols for networks of dynamic agents with fixed and switching topologies. At each time instant, each agent knows only its and its neighbors’ state, but must reach consensus on a group decision value that is function of all the agents’ initial state.We show that our protocol design is the solution of individual optimizations performed by the agents. This notion suggests a game theoretic interpretation of consensus problems as mechanism design problems. Under this perspective a supervisor entails the agents to reach a consensus by imposing individual objectives. We prove that such objectives can be chosen so that rational agents have a unique optimal proto…
A Priori Methods
1998
In the case of a priori methods, the decision maker must specify her or his preferences, hopes and opinions before the solution process. The difficulty is that the decision maker does not necessarily know beforehand what it is possible to attain in the problem and how realistic her or his expectations are. The working order in these methods is: 1) decision maker, 2) analyst.
Learning Automata-Based Solutions to Stochastic Nonlinear Resource Allocation Problems
2009
“Computational Intelligence” is an extremely wide-ranging and all-encompassing area. However, it is fair to say that the strength of a system that possesses “Computational Intelligence” can be quantified by its ability to solve problems that are intrinsically hard. One such class of NP-Hard problems concerns the so-called family of Knapsack Problems, and in this Chapter, we shall explain how a sub-field of Artificial Intelligence, namely that which involves “Learning Automata”, can be used to produce fast and accurate solutions to “difficult” and randomized versions of the Knapsack problem (KP).
A fuzzy mathematical programming approach to the assessment of efficiency with DEA models
2003
In many real applications, the data of production processes cannot be precisely measured. This is particularly worrying when assessing efficiency with frontier-type models, such as data envelopment analysis (DEA) models, since they are very sensitive to possible data errors. For this reason, the possibility of having available a methodology that allows the analyst to deal with imprecise data becomes an issue of great interest in these contexts. To that end, we develop some fuzzy versions of the classical DEA models (in particular, the BCC model) by using some ranking methods based on the comparison of α-cuts. The resulting auxiliary crisp problems can be solved by the usual DEA software. We…
Non-dominated “trade-off” solutions in television scheduling optimization
2014
The main approaches for the television scheduling design are commonly based on the ratings or revenues maximization objective, and thus, only a single optimal solution can be obtained, corresponding to the best result for the considered objective. Therefore, these approaches lead up to the alternative solutions loss which, even if less effective from the ratings or revenues maximization viewpoint, may be more suitable for the decision maker because of better compromise in relation to factors influencing the decision process. Specifically, such a compromise could be achieved through a suitable “trade-off” between these factors, with reference to the decision context in which the decision mak…
Simultaneous Airline Scheduling
2008
Currently, there are no solution approaches available to construct and optimize airline schedules within a single model. All existing approaches decompose the problem into smaller and less complex subproblems and solve those subproblems separately. This chapter presents a metaheuristic for simultaneous airline scheduling where several different subproblems are integrated into one single optimization model, except for crew scheduling. The problem-specific metaheuristic uses an adaptive procedure for operator selection to allow an efficient choice between a variety of different operators. Experiments are conducted as proof-of-concept and to calibrate free parameters. Comparing different searc…
GRASP and path relinking for the max–min diversity problem
2010
The max-min diversity problem (MMDP) consists in selecting a subset of elements from a given set in such a way that the diversity among the selected elements is maximized. The problem is NP-hard and can be formulated as an integer linear program. Since the 1980s, several solution methods for this problem have been developed and applied to a variety of fields, particularly in the social and biological sciences. We propose a heuristic method-based on the GRASP and path relinking methodologies-for finding approximate solutions to this optimization problem. We explore different ways to hybridize GRASP and path relinking, including the recently proposed variant known as GRASP with evolutionary p…
Optimum plastic design for multiple sets of loads
1974
We study optimum plastic design of structures made up, or conceived as assemblies of finite elements, each having an elemental piece-wise linear rigid-plastic behaviour. Since cost function linearly dependent on design variables are considered, optimization problems in linear programming are encountered. Allowance is made for design dependent mass forces, and for some technological constraints. The design growing process is studied in the case of various sets of alternative applied loads, and the optimality conditions are written in a proper geometrical form which leads to a generalization of the concept of Foulkes mechanism.
An Interactive Evolutionary Multiobjective Optimization Method: Interactive WASF-GA
2015
In this paper, we describe an interactive evolutionary algorithm called Interactive WASF-GA to solve multiobjective optimization problems. This algorithm is based on a preference-based evolutionary multiobjective optimization algorithm called WASF-GA. In Interactive WASF-GA, a decision maker (DM) provides preference information at each iteration simple as a reference point consisting of desirable objective function values and the number of solutions to be compared. Using this information, the desired number of solutions are generated to represent the region of interest of the Pareto optimal front associated to the reference point given. Interactive WASF-GA implies a much lower computational…
Local search based evolutionary multi-objective optimization algorithm for constrained and unconstrained problems
2009
Evolutionary multi-objective optimization algorithms are commonly used to obtain a set of non-dominated solutions for over a decade. Recently, a lot of emphasis have been laid on hybridizing evolutionary algorithms with MCDM and mathematical programming algorithms to yield a computationally efficient and convergent procedure. In this paper, we test an augmented local search based EMO procedure rigorously on a test suite of constrained and unconstrained multi-objective optimization problems. The success of our approach on most of the test problems not only provides confidence but also stresses the importance of hybrid evolutionary algorithms in solving multi-objective optimization problems.