This paper introduces a novel methodology for the optimization, analysis and decision support in production systems development. The methodology is based on the innovization procedure, originally introduced for unveiling new and innovative design principles in engineering design problems. The innovization (innovation via optimization) procedure stretches beyond an optimization task and attempts...

The combination of time division multiple access (TDMA) and non-orthogonal (NOMA), referred to as hybrid TDMA-NOMA system, is considered a potential solution meet the unprecedented requirements for future wireless networks. While recent resource allocation techniques aiming individually maximize either spectral efficiency (SE) or energy (EE), this paper considers an SE-EE trade-off based techni...

Multi-Cluster Very Long Instruction Word (VLIW) architectures are currently designed by using platform-based synthesis techniques. In these approaches, a wide range of platform parameters are tuned to find the best trade-offs in terms of the selected figures of merit (such as energy, delay and area). This optimization phase is called Design Space Exploration (DSE) and it generally consists of a...

to use services transparently in a distributed environment, the utility grids develop a cyber-infrastructure. the parameters of the quality of service such as the allocation-cost and makespan have to be dealt with in order to schedule workflow application tasks in the utility grids. optimization of both target parameters above is a challenge in a distributed environment and may conflict one ano...

This study proposes an expert system, which is called the hybrid Kansei engineering system (HKES) based on multiple affective responses (MARs), to facilitate the development of product form design. An HKES is consists of two sub-systems, namely the forward Kansei engineering system (FKES) and the backward Kansei engineering system (BKES). The FKES is utilized to generate product alternatives an...

in this paper, we proposed an algorithm for solving the problem of task scheduling using particle swarm optimization algorithm, with changes in the selection and removing the guide and also using the technique to get away from the bad, to move away from local extreme and diversity. scheduling algorithms play an important role in grid computing, parallel tasks scheduling and sending them to appr...

An optimal trade-off design for fractional order (FO)-PID controller is proposed with a Linear Quadratic Regulator (LQR) based technique using two conflicting time domain objectives. A class of delayed FO systems with single non-integer order element, exhibiting both sluggish and oscillatory open loop responses, have been controlled here. The FO time delay processes are handled within a multi-o...

The covariance matrix adaptation evolution strategy (CMA-ES) is one of the most powerful evolutionary algorithms for real-valued single-objective optimization. Here a variant of the CMA-ES for multi-objective optimization (MOO) is developed. First a single-objective, elitist CMA-ES using plus-selection and step size control based on a success rule is introduced. This algorithm is compared to th...

Portfolio optimization is a multi-objective problem (MOOP) with risk and profit, or some form of the two, as competing objectives. Single-objective portfolio requires trade-off coefficient to be specified in order balance two Erwin Engelbrecht proposed set-based approach single-objective optimization, namely, particle swarm (SBPSO). SBPSO selects sub-set assets that search space for secondary t...

In real life, there are a lot of Multi-objective Optimization Problem, which is shorted for MOP in the process of people working in production and economic and engineering activities. These problems are often very complex and nonlinear, and even conflicted with each other. When solving these problems, Multi-objective Optimization, shorted for MOO should be done on these issues. For example, for...