Optimization of industrial styrene reactor design for two objectives using the non-dominated sorting genetic algorithm (NSGA) is studied. Both adiabatic and steam-injected reactors are considered. The two objectives are maximization of styrene production and styrene selectivity. The study shows that styrene reactor design can be optimized easily and reliably for two objectives by NSGA. It provi...

Among numerous multi-objective optimization algorithms, the Elitist non-dominated sorting genetic algorithm (NSGA-II) is one of the most popular methods due to its simplicity, effectiveness and minimum involvement of the user. This article develops a multi-objective variation of the Nelder-Mead simplex method and combines it with NSGA-II in order to improve the quality and spread of the solutio...

Task scheduling plays an important part in the improvement of parallel and distributed systems. The problem of task scheduling has been shown to be NP hard. The time consuming is more to solve the problem in deterministic techniques. There are algorithms developed to schedule tasks for distributed environment, which focus on single objective. The problem becomes more complex, while considering ...

A method for computing minimum cost trajectory planning for industrial robot manipulators is presented. The objective function minimizes the cost function with the constraints being joint positions, velocities, jerks and torques by considering dynamic equations of motion. A clamped cubic spline is used to represent the trajectory. This is a non-linear constrained optimization problem. The probl...

Mixed-model U-shaped assembly line balancing problems (MMUALBP) is known to be NP-hard resulting in it being nearly impossible to obtain an optimal solution for practical problems with deterministic algorithms. This paper presents a new evolutionary method called combinatorial optimisation with coincidence algorithm (COIN) being applied to Type I problems of MMUALBP in a just-in-time production...

In Multi-objective Optimization the goal is to present a set of Pareto-optimal solutions to the decision maker (DM). One out of these solutions is then chosen according to the DM preferences. Given that the DM has some general idea of what type of solution is preferred, a more efficient optimization could be run. This can be accomplished by letting the optimization algorithm make use of this pr...

Robotic systems, whether physical or virtual, must balance multiple objectives to operate effectively. Beyond performance metrics such as speed and turning radius, efficiency of movement, stability, and other objectives contribute to the overall functionality of a system. Optimizing multiple objectives requires algorithms that explore and balance improvements in each. In this paper, we evaluate...

The design of an urban water distribution system (WDS) is a challenging problem involving multiple objectives. The goal of robust multi-objective optimization for WDS design is to find the set of solutions which embodies an acceptable trade-off between system cost and reliability, so that the ideal solution may be selected for a given budget. In addition to satisfying consumer needs, a system m...