Multi-objective particle swarm optimisation based integrated production inventory routing planning for efficient perishable food logistics operations

Sustainable and efficient food supply chain has become an essential component of one’s life. The model proposed in this paper is deeply linked to people's quality of life as a result of which there is a large incentive to fulfil customer demands through it. This proposed model can enhance food quality by making the best possible food quality accessible to customers, construct a sustainable logistics system considering its environmental impact and ensure the customer demand to be fulfilled as fast as possible. In this paper, an extended model is examined that builds a unified planning problem for efficient food logistics operations where four important objectives are viewed: minimising the total expense of the system, maximising the average food quality along with the minimisation of the amount of CO₂ emissions in transportation along with production and total weighted delivery lead time minimisation. A four objective mixed integer linear programming model for intelligent food logistics system is developed in the paper. The optimisation of the formulated mathematical model is proposed using a modified multi-objective particle swarm optimisation algorithm with multiple social structures: MO-GLNPSO (Multi-Objective Global Local Near-Neighbour Particle Swarm Optimisation). Computational results of a case study on a given dataset as well as on multiple small, medium and large-scale datasets followed by sensitivity analysis show the potency and effectiveness of the introduced method. Lastly, there has been a scope for future study displayed which would lead to the further progress of these types of models.     

Pixel clustering for color image segmentation

Programming and Computer Software - Image segmentation using a hierarchical sequence of piecewise constant approximations that minimally differ from the original image in terms of the total squared...     

Characterization of a Tryptophan 6-Halogenase from Streptomyces albus and Its Regioselectivity Determinants

Tryptophan halogenases are found in diverse organisms and catalyze regiospecific halogenation. They play an important role in the biosynthesis of halogenated indole alkaloids, which are biologically active and of therapeutic importance. Here, a tryptophan 6-halogenase (SatH) from Streptomyces albus was characterized by using a whole-cell reaction system in Escherichia coli. SatH showed substrate specificity for chloride and bromide ions, leading to regiospecific halogenation at the C6-position of l -tryptophan. In addition, SatH exhibited higher performance in bromination than that of previously reported tryptophan halogenases in the whole-cell reaction system. Through structure-based protein mutagenesis, it has been revealed that two consecutive residues, A78/V79 in SatH and G77/I78 in PyrH, are key determinants in the regioselectivity difference between tryptophan 6- and 5-halogenases. Substituting the AV with GI residues switched the regioselectivity of SatH by moving the orientation of tryptophan. These data contribute to an understanding of the key residues that determine the regioselectivity of tryptophan halogenases.