Fusion of Two Metaheuristic Approaches to Solve the Flight Gate Assignment Problem

AbstractOne of the most important activity in airport operations is the gate scheduling. It is concerned with finding an assignment of flights to terminal and ramp positions (gates), and an assignment of the start and completion times of the processing of a flight at its position. The objectives related to the flight gate assignment problem (FGAP) include the minimization of the number of flights assigned to remote terminals and the minimization of the total walking distance. The main aim of this research is to find a methodology to solve the FGAP. In this paper, we propose a hybrid approach called Biogeography-based Bee Colony Optimization (B-BCO). This approach is obtained fusing two metaheuristics: biogeography-based (BBO) and bee colony optimization (BCO) algorithms. The proposed B-BCO model integrates the BBO migration operator into to bee's search behaviour. Results highlight better performances of the proposed approach in solving FGAP when compared to BCO

Optimising the climate resilience of shipping networks

Climate catastrophes (e.g. hurricane, flooding and heat waves) are generating increasing impact on port operations and hence configuration of shipping networks. This paper formulates the routing problem to optimise the resilience of shipping networks, by taking into account the disruptions due to climate risks to port operations. It first describes a literature review with the emphasis on environmental sustainability, port disruptions due to climate extremes and routing optimisation in shipping operations. Second, a centrality assessment of port cities by a novel multi-centrality-based indicator is implemented. Third, a climate resilience model is developed by incorporating the port disruption days by climate risks into shipping route optimisation. Its main contribution is constructing a novel methodology to connect climate risk indices, centrality assessment, and shipping routing to observe the changes of global shipping network by climate change impacts

Modelling Dry Port Systems in the Framework of Inland Waterway Container Terminals

Overcoming the global sustainability challenges of logistics requires applying solutions that minimize the negative effects of logistics activities. The most efficient way of doing so is through intermodal transportation (IT). Current IT systems rely mostly on road, rail, and sea transport, not inland waterway transport. Developing dry port (DP) terminals has been proven as a sustainable means of promoting and utilizing IT in the hinterland of seaport container terminals. Conventional DP systems consolidate container flows from/to seaports and integrate road and rail transportation modes in the hinterland which improves the sustainability of the whole logistics system. In this article, to extend literature on the sustainable development of different categories of IT terminals, especially DPs, and their varying roles, we examine the possibility of developing DP terminals within the framework of inland waterway container terminals (IWCTs). Establishing combined road–rail–inland waterway transport for observed container flows is expected to make the IT systems sustainable. As such, this article is the first to address the modelling of such DP systems. After mathematically formulating the problem of modelling DP systems, which entailed determining the number and location of DP terminals for IWCTs, their capacity, and their allocation of container flows, we solved the problem with a hybrid metaheuristic model based on the Bee Colony Optimisation (BCO) algorithm and the measurement of alternatives and ranking according to compromise solution (i.e., MARCOS) multi-criteria decision-making method. The results from our case study of the Danube region suggest that planning and developing DP terminals in the framework of IWCTs can indeed be sustainable, as well as contribute to the development of logistics networks, the regionalisation of river ports, and the geographic expansion of their hinterlands. Thus, the main contributions of this article are in proposing a novel DP concept variant, mathematically formulating the problems of its modelling, and developing an encompassing hybrid metaheuristic approach for treating the complex nature of the problem adequately

Swarm Intelligent in Bio-Inspired Perspective: A Summary

This paper summarizes the research performed in the field of swarm intelligent in recent years. The classification of swarm intelligence based on behavior is introduced.  The principles of each behaviors, i.e. foraging, aggregating, gathering, preying, echolocation, growth, mating, clustering, climbing, brooding, herding, and jumping are described. 3 algorithms commonly used in swarm intelligent are discussed.  At the end of summary, the applications of the SI algorithms are presented

Swarm Intelligent in Bio-Inspired Perspective: A Summary

This paper summarizes the research performed in the field of swarm intelligent in recent years. The classification of swarm intelligence based on behavior is introduced. The principles of each behaviors, i.e. foraging, aggregating, gathering, preying, echolocation, growth, mating, clustering, climbing, brooding, herding, and jumping are described. 3 algorithms commonly used in swarm intelligent are discussed. At the end of summary, the applications of the SI algorithms are presented

2D Swarm Meerkats Behavior Modelling

Animal behavior is the connection or link between the molecular and physiological aspects of biology and the ecological. Behavior is the bridge between organisms and environment also between the nervous system and the ecosystem. Besides that, behavior is generally the animal's "first line of defense" in response to environmental change. Therefore, careful observation of the behavior can provide us a great information. Behavior is one of the most important features of animal life. As a human, behavior plays a critical role in our lives. This is because behavior is the part of an organism that interacts with its environment. Many problems occur in human society are often related to the interaction between environment or genetics with behavior. The fields of socioecology and animal behavior deal with the issue of environment behavioral interactions at an accurate level and a proximate level. Therefore, social scientists are turning to animal behavior as a framework to interpret human society and to find out possible sources of societal problems. In this study, the foraging behavior of Meerkat will be studied. In this thesis, the foraging behavior of Meerkat will be studied and the parameters for simulation of Meerkats foraging behavior are designed. The designed parameters including the number of agents, number of group, range of perception and number of food. However, there are not much works done on Meerkats therefore, survey form is used in designing these 14 sets of parameters. Only the choices that have higher percentage is focused in designing the 14 sets of parameters for simulation. The performance of each 14 sets of simulation are compared based on the result obtained from the simulations such as the highest mean quality the simulation can achieve and the number of ticks required to reach the highest mean quality. The higher the mean quality the better the performance. The smaller the number of ticks required to reach the highest mean quality the better the performance

Designing of stand-alone hybrid PV/wind/battery system using improved crow search algorithm considering reliability index

Abstract In this paper, the design of a hybrid renewable energy PV/wind/battery system is proposed for improving the load supply reliability over a study horizon considering the Net Present Cost (NPC) as the objective function to minimize. The NPC includes the costs related to the investment, replacement, operation, and maintenance of the hybrid system. The considered reliability index is the deficit power-hourly interruption probability of the load demand. The decision variables are the number of PV panels, wind turbines and batteries, capacity of transferred power by inverter, angle of PV panels, and wind tower height. To solve the optimization problem, a new algorithm named improved crow search algorithm (ICSA) is proposed. The design of the system is done for Zanjan city, Iran based on real data of solar radiation and wind speed of this area. The performance of the proposed ICSA is compared with crow search algorithm (CSA) and particle swarm optimization methods in different combinations of system. This comparison shows that the proposed ICSA algorithm has better performance than other methods