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In this paper the synthesis of linear array geometry with minimum side lobe level using a new class of Particle Swarm Optimization technique namely Improved Particle Swarm Optimization (IPSO) is described. The IPSO algorithm is a newly proposed, high-performance evolutionary algorithm capable of solving general N-dimensional, linear and nonlinear optimization problems. Compared to other evolutionary...
The multi-level lot-sizing (MLLS) problem has been widely studied but still plays an important role in the efficient operation of modern manufacturing and assembly processes. The MLLS problem without restrictive assumption on the product structure is difficult to be solved because it is NP-hard and the situation is even exacerbated by the increasing structure complexity of modern products. Several...
This paper presents a comprehensive survey of many evolutionary algorithms for solving multiobjective optimization problems. Four main kinds of multiobjective algorithms (GA, PSO, SA, and AC) have been presented, and their merits and demerits are compared and discussed respectively. Finally, a mix algorithm is suggested as an effective method.
Scheduling problems are very important for many (research) fields. However only for few instances there are polynomial time optimization algorithms, because the vast majority of scheduling problem instances is NP-hard. In such cases heuristic and/or stochastic algorithm are used which tend toward but do not guarantee the finding of optimal solution. The aim of our paper is to investigate the performance...
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