An optimum design course supported by the particle swarm optimisation algorithm for undergraduate students
نویسنده
چکیده
An optimum design course is being taught to undergraduate students as a basic discipline in engineering and technology education. Optimum design aims primarily at determining the best possible combination of solutions used as design parameters to maximise or minimise an optimisation problem. The development of conventional optimum approaches has dramatically influenced modern teaching technologies. In this article, the author proposes the particle swarm optimisation algorithm for use in an optimum design course. An intensive course on optimum design is supported by the particle swarm optimisation algorithm for undergraduate students. A new concept, combining the particle swarm optimisation algorithm with conventional material, is introduced. Upon completion of this course, students can explain the basic concepts and terminologies associated with particle swarm optimisation. Students can also utilise relevant software on the particle swarm optimisation algorithm in order to solve optimum design problems. Three words can summarise the main features of the proposed approach: faster, cheaper and simpler.
منابع مشابه
A New Solution for the Cyclic Multiple-Part Type Three-Machine Robotic Cell Problem based on the Particle Swarm Meta-heuristic
In this paper, we develop a new mathematical model for a cyclic multiple-part type threemachine robotic cell problem. In this robotic cell a robot is used for material handling. The objective is finding a part sequence to minimize the cycle time (i.e.; maximize the throughput) with assumption of known robot movement. The developed model is based on Petri nets and provides a new method to calcul...
متن کاملIMPROVING COMPUTATIONAL EFFICIENCY OF PARTICLE SWARM OPTIMIZATION FOR OPTIMAL STRUCTURAL DESIGN
This paper attempts to improve the computational efficiency of the well known particle swarm optimization (PSO) algorithm for tackling discrete sizing optimization problems of steel frame structures. It is generally known that, in structural design optimization applications, PSO entails enormously time-consuming structural analyses to locate an optimum solution. Hence, in the present study it i...
متن کاملA COMBINATION OF PARTICLE SWARM OPTIMIZATION AND MULTI-CRITERION DECISION-MAKING FOR OPTIMUM DESIGN OF REINFORCED CONCRETE FRAMES
Structural design optimization usually deals with multiple conflicting objectives to obtain the minimum construction cost, minimum weight, and maximum safety of the final design. Therefore, finding the optimum design is hard and time-consuming for such problems. In this paper, we borrow the basic concept of multi-criterion decision-making and combine it with Particle Swarm Optimi...
متن کاملControl of nonlinear systems using a hybrid APSO-BFO algorithm: An optimum design of PID controller
This paper proposes a novel hybrid algorithm namely APSO-BFO which combines merits of Bacterial Foraging Optimization (BFO) algorithm and Adaptive Particle Swarm Optimization (APSO) algorithm to determine the optimal PID parameters for control of nonlinear systems. To balance between exploration and exploitation, the proposed hybrid algorithm accomplishes global search over the whole search spa...
متن کاملControl of nonlinear systems using a hybrid APSO-BFO algorithm: An optimum design of PID controller
This paper proposes a novel hybrid algorithm namely APSO-BFO which combines merits of Bacterial Foraging Optimization (BFO) algorithm and Adaptive Particle Swarm Optimization (APSO) algorithm to determine the optimal PID parameters for control of nonlinear systems. To balance between exploration and exploitation, the proposed hybrid algorithm accomplishes global search over the whole search spa...
متن کامل