scholarly journals Tramp Ship Routing and Scheduling with Speed Optimization Considering Carbon Emissions

2019 ◽  
Vol 11 (22) ◽  
pp. 6367 ◽  
Author(s):  
Houming Fan ◽  
Jiaqi Yu ◽  
Xinzhe Liu
Keyword(s):  
Carbon Emissions ◽  
Simulated Annealing Algorithm ◽  
Neighborhood Search ◽  
Solution Quality ◽  
Ship Routing ◽  
Routing And Scheduling ◽  
Genetic Simulated Annealing Algorithm ◽  
Speed Optimization ◽  
Ship Scheduling ◽  
The Impact

The International Maritime Organization (IMO) proposed to reduce the total CO2 emissions of the maritime sector by 50% by 2050, and strive to gradually achieve the zero-carbon target. Therefore, shipping companies need to consider environmental impacts while pursuing benefits. In view of the tramp ship scheduling with speed optimization problem, considering carbon emissions, the configuration of owner ships and charter ships, and the impact of sailing speed on ship scheduling with the target of minimizing the total costs of shipping companies, multi-type tramp ship scheduling and speed optimization considering carbon emissions is established. A genetic simulated annealing algorithm based on a variable neighborhood search is proposed to solve the problem. Firstly, the ship type is matched with the cargo. Then the route is generated according to the time constraint, and finally, the neighborhood search strategy is adopted to improve the solution quality. The effectiveness of the proposed model and algorithm is verified by an example, which also confirms that ship scheduling and sailing speed joint optimization can reduce costs and carbon emissions. Research results can not only deepen the study of the theory of tramp scheduling but also to effectively solve the tramp shipping schedule considering carbon emissions problems faced by companies to provide theoretical guidance.

scholarly journals A Heuristic Procedure for a Ship Routing and Scheduling Problem with Variable Speed and Discretized Time Windows

2014 ◽  
Vol 2014 ◽  
pp. 1-13 ◽  
Author(s):  
Krystel K. Castillo-Villar ◽  
Rosa G. González-Ramírez ◽  
Pablo Miranda González ◽  
Neale R. Smith
Keyword(s):  
Time Windows ◽  
Waiting Times ◽  
Neighborhood Search ◽  
Scheduling Problem ◽  
Computational Results ◽  
Solution Quality ◽  
Ship Routing ◽  
Routing And Scheduling ◽  
Ship Routing And Scheduling ◽  
Tramp Shipping

This paper develops a heuristic algorithm for solving a routing and scheduling problem for tramp shipping with discretized time windows. The problem consists of determining the set of cargoes that should be served by each ship, the arrival, departure, and waiting times at each port, while minimizing total costs. The heuristic proposed is based on a variable neighborhood search, considering a number of neighborhood structures to find a solution to the problem. We present computational results, and, for comparison purposes, we consider instances that can be solved directly by CPLEX to test the performance of the proposed heuristic. The heuristics achieves good solution quality with reasonable computational times. Our computational results are encouraging and establish that our heuristic can be utilized to solve large real-size instances.

scholarly journals Optimal Facility Location Model Based on Genetic Simulated Annealing Algorithm for Siting Urban Refueling Stations

2015 ◽  
Vol 2015 ◽  
pp. 1-13 ◽  
Author(s):  
Dawei Chen ◽  
Shun Zhou ◽  
Yuanchang Xie ◽  
Xuhong Li
Keyword(s):  
Simulated Annealing ◽  
Simulated Annealing Algorithm ◽  
Impact Factors ◽  
Location Decisions ◽  
Second Stage ◽  
Genetic Simulated Annealing Algorithm ◽  
Annealing Algorithm ◽  
Two Stages ◽  
Station Location ◽  
The Impact

This paper analyzes the impact factors and principles of siting urban refueling stations and proposes a three-stage method. The main objective of the method is to minimize refueling vehicles’ detour time. The first stage aims at identifying the most frequently traveled road segments for siting refueling stations. The second stage focuses on adding additional refueling stations to serve vehicles whose demands are not directly satisfied by the refueling stations identified in the first stage. The last stage further adjusts and optimizes the refueling station plan generated by the first two stages. A genetic simulated annealing algorithm is proposed to solve the optimization problem in the second stage and the results are compared to those from the genetic algorithm. A case study is also conducted to demonstrate the effectiveness of the proposed method and algorithm. The results indicate the proposed method can provide practical and effective solutions that help planners and government agencies make informed refueling station location decisions.

scholarly journals Near-optimal state assignment in a finite state machine

2021 ◽  
Vol 3 (1) ◽  
pp. 9-16
Author(s):  
Reinaldo Da Silva Ribeiro ◽  
Rafael Lima de Carvalho ◽  
Tiago Da Silva Almeida
Keyword(s):  
Simulated Annealing ◽  
Simulated Annealing Algorithm ◽  
Systems Design ◽  
The State ◽  
Solution Quality ◽  
State Assignment ◽  
Finite State ◽  
Annealing Algorithm ◽  
The Impact

In this research, the application of the Simulated Annealing algorithm to solve the state assignment problem in finite state machines is investigated. The state assignment is a classic NP-Complete problem in digital systems design and impacts directly on both area and power costs as well as on the design time. The solutions found in the literature uses population-based methods that consume additional computer resources. The Simulated Annealing algorithm has been chosen because it does not use populations while seeking a solution. Therefore, the objective of this research is to evaluate the impact on the quality of the solution when using the Simulated Annealing approach. The proposed solution is evaluated using the LGSynth89 benchmark and compared with other approaches in the state-of-the-art. The experimental simulations point out an average loss in solution quality of 14.29%, while an average processing performance of 58.67%. The results indicate that it is possible to have few quality losses with a significant increase in processing performance.

Study on Hybrid Genetic Simulated Annealing Algorithm for Multi-Vehicle and Multi-Cargo Loading Problem

2010 ◽  
Vol 171-172 ◽  
pp. 167-170 ◽  
Author(s):  
Xiao Bo Wang ◽  
Jin Ying Sun ◽  
Chun Yu Ren
Keyword(s):  
Simulated Annealing ◽  
Large Scale ◽  
Simulated Annealing Algorithm ◽  
Solution Quality ◽  
Genetic Simulated Annealing Algorithm ◽  
Algorithm Construct ◽  
Loading Problem ◽  
Annealing Algorithm ◽  
Crossover And Mutation

This paper studies multi-vehicle and multi-cargo loading problem under the limited loading capacity. Hybrid genetic simulated annealing algorithm is used to get the optimization solution. Firstly, adopt hybrid coding so as to make the problem more succinctly. On the basis of cubage-weight balance algorithm, construct initial solution to improve the feasibility. Adopt the improved non-uniform mutation so as to enhance local search ability of chromosomes. Secondly, through utilizing Boltzmann mechanism of simulated annealing algorithm, control crossover and mutation operation of genetic algorithm, search efficiency so as to improve the solution quality of algorithm. Finally, the example can be shown that the above model and algorithm is effective and can provide for large-scale ideas to solve practical problems.

scholarly journals Economic Development, CO2 Emissions and Energy Use Nexus-Evidence from the Danube Region Countries

Energies ◽  
2021 ◽  
Vol 14 (11) ◽  
pp. 3165
Author(s):  
Eva Litavcová ◽  
Jana Chovancová
Keyword(s):  
Economic Growth ◽  
Energy Consumption ◽  
Co2 Emissions ◽  
Carbon Emissions ◽  
Bounds Testing ◽  
Mutual Cooperation ◽  
Long Run ◽  
Short Run ◽  
Danube Region ◽  
The Impact

The aim of this study is to examine the empirical cointegration, long-run and short-run dynamics and causal relationships between carbon emissions, energy consumption and economic growth in 14 Danube region countries over the period of 1990–2019. The autoregressive distributed lag (ARDL) bounds testing methodology was applied for each of the examined variables as a dependent variable. Limited by the length of the time series, we excluded two countries from the analysis and obtained valid results for the others for 26 of 36 ARDL models. The ARDL bounds reliably confirmed long-run cointegration between carbon emissions, energy consumption and economic growth in Austria, Czechia, Slovakia, and Slovenia. Economic growth and energy consumption have a significant impact on carbon emissions in the long-run in all of these four countries; in the short-run, the impact of economic growth is significant in Austria. Likewise, when examining cointegration between energy consumption, carbon emissions, and economic growth in the short-run, a significant contribution of CO2 emissions on energy consumptions for seven countries was found as a result of nine valid models. The results contribute to the information base essential for making responsible and informed decisions by policymakers and other stakeholders in individual countries. Moreover, they can serve as a platform for mutual cooperation and cohesion among countries in this region.

scholarly journals The impact of interconnectors on the GB electricity sector and European carbon emissions

Energy Policy ◽  
2021 ◽  
Vol 151 ◽  
pp. 112170
Author(s):  
Callum MacIver ◽  
Waqquas Bukhsh ◽  
Keith R.W. Bell
Keyword(s):  
Carbon Emissions ◽  
Electricity Sector ◽  
The Impact
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