appropriate scheduling and sequencing of tasks on machines is one of the basic and significant problems that a shop or a factory manager encounters; this is why in recent decades extensive studies have been done on scheduling issues. one type of scheduling problems is just-in-time (jit) scheduling and in this area, motivated by jit manufacturing, this study investigates a mathematical model for...

this paper proposes a method to solve multi-objective problems using improved particle swarm optimization. we propose leader particles which guide other particles inside the problem domain. two techniques are suggested for selection and deletion of such particles to improve the optimal solutions. the first one is based on the mean of the m optimal particles and the second one is based on appoin...

a theorem was recently introduced to establish a relationship betweengoal programming and fuzzy programming for vectormaximum problems.in this short note it is shown that the relationship does not exist underall circumstances. the necessary correction is proposed.

estimation of parameters of a hydrologic model is undertaken using a procedure called “calibration” in order to obtain predictions as close as possible to observed values. this study aimed to use the particle swarm optimization (pso) algorithm for automatic calibration of the hec-hms hydrologic model, which includes a library of different event-based models for simulating the rainfall-runoff pr...

With the increasing complexity of engineering problems, the traditional, single-objective and deterministic optimization method can not meet people’s requirements. A multi-objective fuzzy optimization model of resource input is built for M chlor-alkali chemical eco-industrial park in this paper. First, the model is changed into the form that can be solved by genetic algorithm using fuzzy theory...

In this paper, a new method based on genetic-fuzzy algorithm for multi-objective optimization is proposed. This method is successfully applied to several multi-objective optimization problems. Two examples are presented: the first example is the optimization of two nonlinear mathematical functions and the second one is the design of PI controller for control of an induction motor drive supplie...

Fuzzy clustering methods are conveniently employed in constructing a fuzzy model of a system, but they need to tune some parameters. In this research, FCM is chosen for fuzzy clustering. Parameters such as the number of clusters and the value of fuzzifier significantly influence the extent of generalization of the fuzzy model. These two parameters require tuning to reduce the overfitting in the...

In this paper, an efficient multi-objective model is proposed to solve time-cost trade off problem considering cash flows. The proposed multi-objective meta-heuristic is based on Ant colony optimization and is called Non Dominated Archiving Ant Colony Optimization (NAACO). The significant feature of this work is consideration of uncertainties in time, cost and more importantly interest rate. A ...

In this paper, we introduce the concept of complex multi-fuzzy sets (CMkFSs) as a generalization of the concept of multi-fuzzy sets by adding the phase term to the definition of multi-fuzzy sets. In other words, we extend the range of multi-membership function from the interval [0,1] to unit circle in the complex plane. The novelty of CMkFSs lies in the ability of complex multimembership functi...