in this paper, a new approach based on game theory has been proposed to multi responses problem optimization. game theory is a useful tool for decision making in the conflict of interests between intelligent players in order to select the best joint strategy for them through selecting the best joint desirability. present research uses the game theory approach via definition of each response as ...

Since the introduction of Response Surface Methodology in the 1950s, there have been many developments with the aim of expanding the range of applications of the methodology. Various new design, modeling and optimization techniques have been introduced for coping with unknown input-output relationships, costly or time-consuming experimental studies and irregular experimental regions (e.g., non-...

This paper describes the application of Kriging metamodeling in multiple-objective simulation optimization. An Arenabased simulation model of an (s, S) inventory system is utilized to demonstrate the capabilities of Kriging metamodeling as a simulation tool. Response surface methodology and Kriging metamodeling are compared to determine the situations in which one approach might be preferred ov...

In this study, response surface models (RSMs) based on limited data are developed. Experimental cutting force data for the flat end milling process are employed to build these models. Four RSM models are developed in terms of process variables. The first model is used to build the mean cutting force. Similarly, the second, third and fourth models are used to build models for the variance, skewn...

An optimisation-based iterative design of fixed-structure controllers with frequencydomain criteria is presented. An interactive multiobjective optimisation procedure is presented, which is based on a direct shaping of the frequency responses, without the need to construct explicit weighting filters. At each iteration, a constrained optimisation problem is formulated in such a way that successi...

The most recent approaches of multi-objective optimization constitute application of meta-heuristic algorithms for which, parameter tuning is still a challenge. The present work hybridizes swarm intelligence with fuzzy operators to extend crisp values of the main control parameters into especial fuzzy sets that are constructed based on a number of prescribed facts. Such parameter-less particle ...

The article presents a mathematical model of multi-stage game the process safe control transport object in possible collision situations with other encountered objects, containing description state variables, and constraints, sets permissible strategies. Multi-criteria optimization tasks were formulated form positional matrix games under conditions playing non-cooperative cooperative as well no...

The main aim of the study focuses on the optimizing the response of the PID controllers used typically for temperature control loop in centrifugal machines in sugar industry using soft-computing. The centrifugal machines are used for the filtering sugar and molasses and the whole process is carried out at a certain fixed temperature. Any alterations from the set-point will cause instability in ...

This paper highlights an integrated approach to solve the correlated multi-response optimization problem through a case study in submerged arc welding (SAW). The proposed approach has been presented to overcome different limitations and drawbacks of existing optimization techniques available in literature. Traditional Taguchi optimization technique is based under the assumption that quality res...

In order to improve the fitting accuracy and optimization efficiency of surrogate model, a multi-response weighted adaptive sampling (MWAS) approach based on hybrid model was proposed implemented multi-objective lightweight design car seats. this approach, sample discreteness index in input space calculated by maximum minimum distance (MDA), uncertainty output response strategy prediction varia...