Arijit De

Bio: Arijit De is an academic researcher from Indian Institute of Technology Kharagpur. The author has contributed to research in topics: Materials science & Microstrip. The author has an hindex of 16, co-authored 64 publications receiving 704 citations. Previous affiliations of Arijit De include University of Hong Kong & Loughborough University.

Multiobjective Approach for Sustainable Ship Routing and Scheduling With Draft Restrictions

Abstract: This research addresses the sustainability and safety related challenges associated with the complex, practical, and real-time maritime transportation problem, and proposes a multiobjective mathematical model integrating different shipping operations. A mixed integer nonlinear programming (MINLP) model is formulated considering different maritime operations, such as routing and scheduling of ships, time window concept considering port's high tidal scenario, discrete planning horizon, loading/unloading operation, carbon emission from the vessel, and ship's draft restriction for maintaining the vessel's safety at the port. The relationship between fuel consumption and vessel speed optimization is included in the model for the estimation of the total fuel consumed and carbon emission from each vessel. Time window concept considered in the problem aims to improve the service level of the port by imposing different penalty charges associated with the early arrival of the vessel before the starting of the time window and vessel failing to finish its operation within the allotted time window. Another practical aspect of the maritime transportation such as high tide scenario is included in the model to depict the vessel arrival and departure time at a port. Two novel algorithms—Nondominated sorting genetic algorithm II (NSGA-II) and Multiobjective particle swarm optimization have been applied to solve the multiobjective mathematical model. The illustrative examples inspired from the real-life problems of an international shipping company are considered for application. The experimental results, comparative, and sensitivity analysis demonstrate the robustness of the proposed model.

Hybridizing Basic Variable Neighborhood Search With Particle Swarm Optimization for Solving Sustainable Ship Routing and Bunker Management Problem

Abstract: This paper studies a novel sustainable ship routing problem considering a time window concept and bunker fuel management. Ship routing involves the decisions corresponding to the deployment of vessels to multiple ports and time window concept helps to maintain the service level of the port. Reducing carbon emissions within the maritime transportation domain remains one of the most significant challenges as it addresses the sustainability aspect. Bunker fuel management deals with the fuel bunkering issues faced by different ships, such as selection of bunkering ports and total bunkered amount at a port. A novel mathematical model is developed capturing the intricacies of the problem. A hybrid particle swarm optimization with a basic variable neighborhood search algorithm is proposed to solve the model and compared with the exact solutions obtained using Cplex and other popular algorithms for several problem instances. The proposed algorithm outperforms other popular algorithms in all the instances in terms of the solution quality and provides good quality solutions with an average cost deviation of 5.99% from the optimal solution.

Balancing the economic and environmental performance of maritime transportation (vol 15, pg 458, 2010)

Abstract: This paper looks at the implications of various maritime emissions reductions policies for maritime logistics. There can be important trade-offs that have to be made between the environmental benefits associated with such measures as reduction in steaming speed and change in the number of vessels in the fleet, and more conventional logistics attributes such as in-transit inventory holdings.

A Comprehensive Review on NSGA-II for Multi-Objective Combinatorial Optimization Problems

Abstract: This paper provides an extensive review of the popular multi-objective optimization algorithm NSGA-II for selected combinatorial optimization problems viz. assignment problem, allocation problem, travelling salesman problem, vehicle routing problem, scheduling problem, and knapsack problem. It is identified that based on the manner in which NSGA-II has been implemented for solving the aforementioned group of problems, there can be three categories: Conventional NSGA-II, where the authors have implemented the basic version of NSGA-II, without making any changes in the operators; the second one is Modified NSGA-II, where the researchers have implemented NSGA-II after making some changes into it and finally, Hybrid NSGA-II variants, where the researchers have hybridized the conventional and modified NSGA-II with some other technique. The article analyses the modifications in NSGA-II and also discusses the various performance assessment techniques used by the researchers, i.e., test instances, performance metrics, statistical tests, case studies, benchmarking with other state-of-the-art algorithms. Additionally, the paper also provides a brief bibliometric analysis based on the work done in this study.

Energy efficiency of integrated electric propulsion for ships – A review

Abstract: There has been mounting concerns over energy consumption and environmental impacts due to an increase in worldwide shipping activities. The International Maritime Organization has adopted regulations to impose limits on greenhouse gas emissions originated from fuel combustion of marine vessels. Such regulations are introduced in terms of energy efficiency design index and energy efficiency operational indicator. Extensive electrification of ship propulsion and shipboard power systems has been vastly proposed in the literature to make onboard energy systems more efficient. However, energy efficiency in the context of maritime transport is becoming even more stringent. Various technologies and operational practices therefore are being proposed to ensure full compliance with the tightening restrictions. The methods to increase energy efficiency and environmental performance of all-electric ships to satisfy such requirements involve integration of energy storage with a contribution of intelligent power management to optimize power split between various power generation sources; a tendency toward DC power distribution due to eliminating the need of all generators to be synchronized at a specific frequency; installation of unconventional propulsors for greater maneuverability requirements while keeping fuel consumption low; adoption of low carbon content fuel like liquefied natural gas for dual fuel diesel electric propulsion; establishment of onboard renewable energy systems for alternative clean power options; fuel cell integration in complementary operation with conventional diesel generators. This paper identifies promising technologies and practices that are applicable to onboard energy systems of all-electric ships and also reveals energy efficiency sensitivity of all-electric ships to different applications. The proposed strategies should be eventually combined with alternative technology-based and operational-based measures as implemented on conventional propulsion ships in order to realize full potential for energy efficient operation.