Cumulative Count of Conforming (CCC) charts are utilized for monitoring the quality characteristics in high-quality processes. Executive cost of control charts is a motivation for researchers to design them with the lowest cost. Usually in most researches, only one objective named cost function is minimized subject to statistical constraints, which is not effective method for economic-statistic...

A fractional order (FO) PID or FOPID controller is designed for an Automatic Voltage Regulator (AVR) system with the consideration of contradictory performance objectives. An improved evolutionary Nondominated Sorting Genetic Algorithm (NSGA-II), augmented with a chaotic Henon map is used for the multiobjective optimization based design procedure. The Henon map as the random number generator ou...

Coverage is a fundamental problem in wireless sensor network (WSN), which is defined as the measurement of the quality of surveillance of sensing function. The concerns of coverage optimization are the maximize coverage rate and the minimize energy consumption. In this paper, we proposed the multi-objective evolutionary algorithm based on decomposition with particle swarm optimization (MOEA/D-P...

The automotive deployment problem is a real-world constrained multiobjective assignment problem in which software components must be allocated to processing units distributed around a car’s chassis. Prior work has shown that evolutionary algorithms such as NSGA-II can produce good quality solutions to this problem. This paper presents a population-based ant colony optimisation (PACO) approach t...

This paper presents an evolutionary multi-objective simulation-optimization system for personnel scheduling. The system is developed for the Swedish postal services and aims at finding personnel schedules that minimizes both total man hours and the administrative burden of the person responsible for handling schedules. For the optimization, the multi-objective evolutionary algorithm NSGA-II is ...

Abstract. This paper examines the effect of crossover operations on the performance of EMO algorithms through computational experiments on knapsack problems and flowshop scheduling problems using the NSGA-II algorithm. We focus on the relation between the performance of the NSGA-II algorithm and the similarity of recombined parent solutions. First we show the necessity of crossover operations t...

Existing privacy-preserving evolutionary algorithms are limited to specific problems securing only cost function evaluation. This lack of functionality and security prevents their use for many security sensitive business optimization problems, such as our use case in collaborative supply chain management. We present a technique to construct privacypreserving algorithms that address multi-object...

According to the traditional GA and EDA weakness, on the basis of MMEA, the orthogonal design initialization, convergence criterion and K-means clustering analysis method were introduced in this paper and it proposed a new model multi-objective evolutionary algorithm OMEA. The practice results showed that the OMEA had been greatly improved on both convergence and diversity of the solutions, rea...

Many real world problems require careful balancing of fiscal, technical, and social objectives. Informed negotiation and balancing of objectives can be greatly aided through the use of evolutionary multiobjective optimization (EMO) algorithms, which can evolve entire tradeoff (or Pareto) surfaces within a single run. The primary difficulty in using these methods lies in the large number of para...

Algorithms developed for scheduling applications on heterogeneous multiprocessor system focus on a single objective such as execution time, cost or total data transmission time. However, if more than one objective (e.g. execution cost and time, which may be in conflict) are considered, then the problem becomes more challenging. This project is proposed to develop a multiobjective scheduling alg...