A heuristic optimization approach for multi-vehicle and one-cargo green transportation scheduling in shipbuilding

2021 ◽  
Vol 49 ◽  
pp. 101306
Author(s):  
Zuhua Jiang ◽  
Yini Chen ◽  
Xinyu Li ◽  
Baihe Li
Keyword(s):  
Heuristic Optimization ◽  
Optimization Approach ◽  
Green Transportation ◽  
Transportation Scheduling

scholarly journals Heuristic Optimization of Overloading Due to Electric Vehicles in a Low Voltage Grid

Energies ◽  
2020 ◽  
Vol 13 (22) ◽  
pp. 6069
Author(s):  
Sajjad Haider ◽  
Peter Schegner
Keyword(s):  
Electric Vehicles ◽  
Low Voltage ◽  
Optimization Methods ◽  
Monte Carlo Analysis ◽  
Heuristic Optimization ◽  
Optimization Approach ◽  
Worst Case ◽  
Voltage Drops ◽  
The Individual ◽  
Nodal Voltage

It is important to understand the effect of increasing electric vehicles (EV) penetrations on the existing electricity transmission infrastructure and to find ways to mitigate it. While, the easiest solution is to opt for equipment upgrades, the potential for reducing overloading, in terms of voltage drops, and line loading by way of optimization of the locations at which EVs can charge, is significant. To investigate this, a heuristic optimization approach is proposed to optimize EV charging locations within one feeder, while minimizing nodal voltage drops, cable loading and overall cable losses. The optimization approach is compared to typical unoptimized results of a monte-carlo analysis. The results show a reduction in peak line loading in a typical benchmark 0.4 kV by up to 10%. Further results show an increase in voltage available at different nodes by up to 7 V in the worst case and 1.5 V on average. Optimization for a reduction in transmission losses shows insignificant savings for subsequent simulation. These optimization methods may allow for the introduction of spatial pricing across multiple nodes within a low voltage network, to allow for an electricity price for EVs independent of temporal pricing models already in place, to reflect the individual impact of EVs charging at different nodes across the network.

scholarly journals A robust-heuristic optimization approach to a green supply chain design with consideration of assorted vehicle types and carbon policies under uncertainty

2021 ◽  
Author(s):  
Zahra Homayouni ◽  
Mir Saman Pishvaee ◽  
Hamed Jahani ◽  
Dmitry Ivanov
Keyword(s):  
Supply Chains ◽  
Large Scale ◽  
Programming Model ◽  
Supply Chain Design ◽  
Heuristic Optimization ◽  
Optimization Approach ◽  
Economic Uncertainty ◽  
Cap And Trade ◽  
Sustainable Logistics ◽  
Goal Programming Model

AbstractAdoption of carbon regulation mechanisms facilitates an evolution toward green and sustainable supply chains followed by an increased complexity. Through the development and usage of a multi-choice goal programming model solved by an improved algorithm, this article investigates sustainability strategies for carbon regulations mechanisms. We first propose a sustainable logistics model that considers assorted vehicle types and gas emissions involved with product transportation. We then construct a bi-objective model that minimizes total cost as the first objective function and follows environmental considerations in the second one. With our novel robust-heuristic optimization approach, we seek to support the decision-makers in comparison and selection of carbon emission policies in supply chains in complex settings with assorted vehicle types, demand and economic uncertainty. We deploy our model in a case-study to evaluate and analyse two carbon reduction policies, i.e., carbon-tax and cap-and-trade policies. The results demonstrate that our robust-heuristic methodology can efficiently deal with demand and economic uncertainty, especially in large-scale problems. Our findings suggest that governmental incentives for a cap-and-trade policy would be more effective for supply chains in lowering pollution by investing in cleaner technologies and adopting greener practices.

A Shuffled Frog Leaping Algorithm for Solving Vehicle Routing Problem

2012 ◽  
Vol 197 ◽  
pp. 529-533 ◽  
Author(s):  
Kai Ping Luo
Keyword(s):  
Vehicle Routing ◽  
Vehicle Routing Problem ◽  
High Efficiency ◽  
Heuristic Optimization ◽  
Optimization Approach ◽  
Shuffled Frog Leaping Algorithm ◽  
Routing Problem ◽  
Shuffled Frog Leaping ◽  
Encoding Method ◽  
Nearest Neighborhood

For vehicle routing problem, its model is easy to state and difficult to solve. The shuffled frog leaping algorithm is a novel meta-heuristic optimization approach and has strong quickly optimal searching power. The paper applies herein this algorithm to solve the vehicle routing problem; presents a high-efficiency encoding method based on the nearest neighborhood list; improves evolution strategies of the algorithm in order to keep excellent characteristics of the best frog. This proposed algorithm provides a new idea for solving VRP.

scholarly journals Heuristic Optimization Approach to Selecting a Transport Connection in City Public Transport

2017 ◽  
Vol 7 (1) ◽  
pp. 1-5 ◽  
Author(s):  
Jozef Kul’ka ◽  
Martin Mantič ◽  
Melichar Kopas ◽  
Eva Faltinová ◽  
Daniel Kachman
Keyword(s):  
Transport System ◽  
Public Transport ◽  
Slovak Republic ◽  
Heuristic Optimization ◽  
Optimization Approach ◽  
The Public ◽  
Transport Services ◽  
The Individual ◽  
Solution Focused ◽  
Bus Transport

AbstractThe article presents a heuristic optimization approach to select a suitable transport connection in the framework of a city public transport. This methodology was applied on a part of the public transport in Košice, because it is the second largest city in the Slovak Republic and its network of the public transport creates a complex transport system, which consists of three different transport modes, namely from the bus transport, tram transport and trolley-bus transport. This solution focused on examining the individual transport services and their interconnection in relevant interchange points.

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