An MCM's increased throughput and dense circuitry can easily result in failure if the board contains \hot spots". Therefore, an accurate thermal model of an MCM was needed in the development of a new placement algorithm designed to consider both total net length and heat constraints. This algorithm uses a combination of simulated evolution and simulated annealing in an iterative approach. The t...

In this paper, a novel multilink selection framework is developed for different applications with various quality of service (QoS) requirements in avionic systems, based on the multi-attribute decision-making model. Two metaheuristic algorithms are proposed to solve model while optimizing performances. Multilink configuration and multi-homing capabilities generally required aircrafts operating ...

projects scheduling by the project portfolio selection, something that has its own complexity and its flexibility, can create different composition of the project portfolio. an integer programming model is formulated for the project portfolio selection and scheduling.two heuristic algorithms, genetic algorithm (ga) and simulated annealing (sa), are presented to solve the problem. results of cal...

In this paper we present the results of an investigation of the possibilities offered by three wellknown metaheuristic algorithms to solve the timetable problem, a multi-constrained, NP-hard, combinatorial optimization problem with real-world applications. First, we present our model of the problem, including the definition of a hierarchical structure for the objective function, and of the neig...

Particle swarm and simulated annealing optimization algorithms proved to be valid in finding a global optimum in the bound constrained optimization context. However, their original versions can only detect one global optimum even if the problem has more than one solution. In this paper we propose modifications to both algorithms. In the particle swarm optimization algorithm we introduce gradien...

Bilevel programming, a tool for modeling decentralized decision problems, consists of the objective of the leader at its first level and that of the follower at the second level. Bilevel programming has been proved to be an Np-hard problem. Numerous algorithms have been developed for solving bilevel programming problems. These algorithms lack the required efficiency for solving a real problem. ...

The layout design problem is a kind of nesting problems that is naturally NP-hard and very difficult to solve. Layout designing of machine is even more difficult because of its nesting items are actually machine parts that have both irregular shapes and complex constraints. A feasible way to solve machine layout problem is to employ ameliorative algorithms, such as simulated annealing algorithm...

In single-objective optimization it is possible to find a global optimum, while in the multi-objective case no optimal solution is clearly defined, but several that simultaneously optimize all the objectives. However, the majority of this kind of problems cannot be solved exactly as they have very large and highly complex search spaces. Recently, meta-heuristic approaches have become important ...

in financial matters, portfolio can be interpreted as a combination or a series of investments hold by an institution or a person. portfolio optimization is one of the most important concerns of investors for maximizing the portfolio in financial markets. the formation of portfolio is a vital and critical decision for the companies.  in fact, the selection of portfolio is to specify the capital...