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A hybrid flow shop (HFS) scheduling is characterized of “[Formula: see text]” jobs “[Formula: see text]” machines with “[Formula: see text]” stages by unidirectional flow of work with a variety of jobs being processed sequentially in a single-pass manner. The HFS scheduling problem is known to be strongly NP-hard in nature. Hence, the essential complexity of the problem necessitates the application of meta-heuristics to solve HFS scheduling problems. A population-based genetic algorithm (GA) and a simulated annealing (SA) algorithm have been proposed to solve the multi-stage HFS scheduling problem with missing operations to minimize the mean tardiness. The computational results observed that the GA is efficient in finding out good quality solutions.

The mix of two different type of fibres, one is natural and another one is synthetic fibres were employed as reinforcing media in this study, and epoxy based polymer resin was employed as the matrix phase. S-glass and luffa fibres had been bonded with epoxy matrix to create a novel composite by compression moulding and to measure the effect of this hybridization in composite laminate utilising five different sequencing. To determine the mechanical characteristics of this composite material using tensile, flexural, and compression strength, a specimen named 'SL4' had shown the highest mechanical strength, resulting in a tensile properties of 253 MPa, compression strength of 234 MPa, and flexural characteristics of 237 MPa. The increment in mechanical characteristics is found to exhibiting around 20% increase comparing to the specimen having next higher value in all the properties. The results evidenced that the presence of luffa fibre layers at the interior most portion of the composite displayed the progressive values in all the investigated mechanical characteristics.

The two-stage Hybrid flow shop (HFS) scheduling is characterized n jobs m machines with two-stages in series. The essential complexities of the problem need to solve the hybrid flow shop scheduling using meta-heuristics. The paper addresses two-stage hybrid flow shop scheduling problems to minimize the makespan time with the batch size of 100 using Genetic Algorithm (GA) and Simulated Annealing algorithm (SA). The computational results observed that the GA algorithm is finding out good quality solutions than SA with lesser computational time.