Most real optimization problems often involve multiple objectives to optimize. In single-objective optimization there exists a global optimum, while in the multi-objective case no optimal solution is clearly defined but rather a set of solutions, so called Pareto-optimal set. Thus, the goal of multi-objective strategies is to obtain an approximation to this set. However, the majority of this ki...

The image reconstruction from the Electrical Impedance Tomography (EIT) can be approached as an optimization problem, in which is desired to minimize the Euclidean distance between the potential values measured in the cross section of the body and the calculated values, for every pattern of current applied, through the modelling of the problem by the Finite Elements Method (FEM). It’s known, a ...

*Subhamoy Chakraborti AVP – IT, Magma Fincorp Limited, India Email: [email protected] Sugata Sanyal Member, School of Computing and Informatics' "Brain Trust" University of Louisiana at Lafayette, USA [email protected] *Corresponding author --------------------------------------------------------------------ABSTRACT------------------------------------------------------------Internet...

In this paper we study algorithms for minimizing the worst-case cost of any agent in a multi-robot team in timecritical missions. We propose a generalized model for flexible mission planning, using hierarchical task networks as the planning framework, and the multiple traveling salesman problem as the cost model for task allocation. Two approximated solutions are provided and compared for this ...

This research explores the use of the modular open systems approach (MOSA) as a method for implementing an evolutionary acquisition strategy as well as the implications of using such an approach on the contracting process. A background on evolutionary acquisition is provided highlighting the benefit of rapid development and production of weapon systems incrementally, with each increment providi...

Scheduling for the flexible job shop is very important in both fields of production management and combinatorial optimization. However, it quit difficult to achieve an optimal solution to this problem with traditional optimization approaches owing to the high computational complexity. The combining of several optimization criteria induces additional complexity and new problems. In this paper, a...

Optimal expansion of medium-voltage power networks is a common issue in electrical distribution planning. Minimizing total cost of the objective function with technical constraints and reliability limits, make it a combinatorial problem which should be solved by optimization algorithms. This paper presents a new hybrid simulated annealing and tabu search algorithm for distribution network expan...

Simulated annealing is a popular local search meta-heuristic used to address discrete and, to a lesser extent, continuous optimization problems. The key feature of simulated annealing is that it provides a means to escape local optima by allowing hill-climbing moves (i.e., moves which worsen the objective function value) in hopes of finding a global optimum. A brief history of simulated anneali...

Placement of multiple dies on an MCM substrate is a difficult combinatorial task in which multiple criteria need to be considered simultaneously to obtain a true multi-objective optimization. Our design methodologies consider multi-objective component placement based on thermal reliability, routing length and chip area criteria for multi-chip module. The purpose of the multi-objective optimizat...

appropriate scheduling and sequencing of tasks on machines is one of the basic and significant problems that a shop or a factory manager encounters; this is why in recent decades extensive studies have been done on scheduling issues. one type of scheduling problems is just-in-time (jit) scheduling and in this area, motivated by jit manufacturing, this study investigates a mathematical model for...