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This paper proposes the implementation of a very simple but efficient fuzzy logic based algorithm to detect the edges of an image with desired level of threshold values. The approach begins by scanning the images using floating 2x2 pixel window. FIS is designed with 4 inputs, whose output is further used in proposed algorithm to reduce the noise in the edges produced by the FIS. This algorithm is compared with six standard algorithms and one more system is also proposed which gives the direct comparison of these six algorithms visually.

Job shop scheduling problem belongs to a class of NP-Hard problems. Hence, finding an optimal solution for this problem is a difficult task. In this study, a hybrid method consisting of Genetic Algorithm (GA) and Differential Evolution (DE) algorithm has been proposed for solving the Job Shop Scheduling problem (JSSP). These algorithms are evolutionary algorithms for solving optimization problems which refine the candidate solutions iteratively. The results of previous studies show that the application of genetic algorithm and differential evolution algorithm individually for this problem yield results close to the upper bounds. The proposed algorithm implemented in MATLAB R2013a uses minimization of makespan as the objective function. This algorithm has been tested on 50 instances of Taillard series (TA01-50) benchmark problem. The simulation results obtained by the proposed algorithm are better than those obtained by the IPSO-TSAB algorithm.