‘The micro/nano reinforced particle’ aluminum metal matrix composites (Al-MMCs) are widely used in manufacturing sector due to light-weight, superior strength-to-weight ratio, better fracture toughness, improved fatigue, and tensile property, enhanced corrosion resistance to harsh environment, etc. This article provides an overview of the manufacturing processes and different reinforcing elements used during the synthesis of Al-MMCs. Generally, the reinforced particles like carbides, nitrides, and compounds of oxides are used. Different organic, inorganic, industrial and agricultural waste which can be used for reinforcement in the aluminum matrix is highlighted with their feasible applications. The common mechanical properties (i.e. hardness, tensile and compressive strength, etc.) reported by different researchers are thoroughly discussed with the aim to highlight the amount of reinforcement and improvement occurred during processing. The formation and methodology for mixing condition and sintering behaviour of Al-MMCs are discussed to impart knowledge about the processing circumstances in powder metallurgical route. The affecting conditions during operating and responsible factor for the tribological behaviour are deliberated in a precise manner to recognize the potentiality of reinforcing particles in Al-MMCs. Finally, the different shortcomings and future prospects of the Al-MMCs are given to encourage the future research directions.

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This paper investigates the dynamic ship berth allocation problem for a container handling port, focusing on vessel waiting time at the anchorage due to the unavailability of the berth and quay cranes. A mixed integer linear programming model (MINLP) considering the fuel cost associated with waiting time and operational time of the docked vessel is developed. The hiring of the quay cranes to load/unload the containers from the ship and arrangement of the vessels in different berths is taken into account. Fuel consumed by the vessels while performing their respective port operations is incorporated in the model for addressing the sustainability aspects in berth allocation problem. A Chemical Reaction Optimization Algorithm (CRO) is proposed to solve the problem in a large-scale realistic environment and compared with the results with Block-Based Genetic Algorithm (BBGA), Genetic Algorithm (GA) and Particle Swarm Optimization (PSO). The computational experiment illustrates and validates the proposed model on a real case scenario of the port located in India. The case shows that the developed model achieves better utilization of port resources and available berths.

An inventory transportation problem of manufacturing organization focusing on several stakeholders such as manufacturers, distributors, wholesalers, retailers and customers is addressed in this paper. The research study considered multi-echelon, multi-product, multimodal and multi-period scenario. The mathematical model in the form of mixed integer nonlinear programming is formulated to minimize the total cost associated with transportation, inventory holding and operational activities. A mathematical formulation based heuristic approach, which comprises of four algorithms, is proposed for solving purpose. The proposed heuristic approach considers the behavioural tendencies of stakeholders pertaining to the selection of shipment routes, transportation mode choice decisions and amount of products to be shipped. Fifteen practical problem instances are solved by using the developed heuristic approach while considering the behavioural aspects of stakeholders. Insights obtained from results will be beneficial for manufacturing organizations in making informed decisions related to transportation planning considering stakeholder's behavioural tendencies.

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