scholarly journals Truck Scheduling Problem Considering Carbon Emissions under Truck Appointment System

2019 ◽  
Vol 11 (22) ◽  
pp. 6256 ◽  
Author(s):  
Fan ◽  
Ren ◽  
Guo ◽  
Li
Keyword(s):  
Carbon Emissions ◽  
Hybrid Genetic Algorithm ◽  
Operation Time ◽  
Neighborhood Search ◽  
Scheduling Problem ◽  
Low Carbon ◽  
Scheduling Scheme ◽  
Truck Scheduling ◽  
Appointment System ◽  
Truck Appointment System

Aiming at the truck scheduling problem between the outer yard and multi-terminals, the appointment optimization model of truck is established. In this model, the queue time and the operation time of truck during the appointment period of different terminals are different. Under the restriction of given appointment quotas of each appointment period, determine the arrival amount of trucks in each appointment period. The goal is to reduce carbon emissions and total costs, improve the efficiency of truck scheduling. To solve this model, hybrid genetic algorithm with variable neighborhood search was designed. Firstly, generate chromosomes, and the front part of the chromosome represents the demand for 40 ft containers and the back part represents the demand for 20 ft containers. Then, the route is generated according to the time constraint and appointment quotas of each appointment period. Finally, the neighborhood search strategy is adopted to improve the solution quality. The validity of the model and algorithm were verified by an example. A low-carbon scheduling scheme was obtained under truck appointment system. The results show that the scheduling scheme under truck appointment system uses fewer trucks, improves the efficiency of delivery, reduces the total costs, and it takes into account the requirements of low carbon.

scholarly journals Lane Allocation Optimization in Container Seaport Gate System Considering Carbon Emissions

2021 ◽  
Vol 13 (7) ◽  
pp. 3628
Author(s):  
Zhihong Jin ◽  
Xin Lin ◽  
Linlin Zang ◽  
Weiwei Liu ◽  
Xisheng Xiao
Keyword(s):  
Branch And Bound ◽  
Carbon Emissions ◽  
Integer Program ◽  
Arrival Times ◽  
Proposed Model ◽  
Gate System ◽  
Appointment System ◽  
Truck Appointment System ◽  
Gate Congestion ◽  
Allocation Decisions

Long queues of arrival trucks are a common problem in seaports, and thus, carbon emissions generated from trucks in the queue cause environmental pollution. In order to relieve gate congestion and reduce carbon emissions, this paper proposes a lane allocation framework combining the truck appointment system (TAS) for four types of trucks. Based on the distribution of arrival times obtained from the TAS, lane allocation decisions in each appointment period are determined in order to minimize the total cost, including the operation cost and carbon emissions cost. The resultant optimization model is a non-linear fractional integer program. This model was firstly transformed to an equivalent integer program with bilinear constraints. Then, an improved branch-and-bound algorithm was designed, which includes further transforming the program into a linear program using the McCormick approximation method and iteratively generating a tighter outer approximation along the branch-and-bound procedure. Numerical studies confirmed the validity of the proposed model and algorithm, while demonstrating that the lane allocation decisions could significantly reduce carbon emissions and operation costs.

scholarly journals Research on Berth-Quay Crane Joint Scheduling Considering Carbon Emission

2021 ◽  
pp. 1-6
Author(s):  
Rui Yang ◽  
◽  
Junqing Sun
Keyword(s):  
Carbon Emissions ◽  
Carbon Dioxide Emissions ◽  
Carbon Emission ◽  
Programming Model ◽  
Container Terminal ◽  
Optimal Scheduling ◽  
Mixed Integer ◽  
Scheduling Problem ◽  
Scheduling Scheme ◽  
Elite Strategy

With the increasing awareness of environmental protection, all walks of life a are paying more and more attention to the carbon dioxide emissions brought by their own industries. For the container terminal, a large proportion of carbon emissions come from the fuel consumption of vessels. In this paper, the consideration of carbon emissions is added to the original berth quay crane joint scheduling problem, and the constraints such as vessel preference for berths and quay crane interference are added. A dual-objective nonlinear mixed integer programming model is established to minimize carbon emissions and minimize costs. The model is solved by the Non-Dominated Sorting Genetic Algorithm with Elite Strategy, and the optimal scheduling scheme is obtained. Finally, the calculation examples are verified to prove the effectiveness and practicability of the model and algorithm.

scholarly journals A Hybrid Genetic Algorithm for Satellite Image Downlink Scheduling Problem

2018 ◽  
Vol 2018 ◽  
pp. 1-11 ◽  
Author(s):  
Bingyu Song ◽  
Feng Yao ◽  
Yuning Chen ◽  
Yingguo Chen ◽  
Yingwu Chen
Keyword(s):  
Genetic Algorithm ◽  
Time Window ◽  
Satellite Image ◽  
Hybrid Genetic Algorithm ◽  
Neighborhood Search ◽  
Scheduling Problem ◽  
Satellite Mission ◽  
Downlink Scheduling ◽  
The Given

The satellite image downlink scheduling problem (SIDSP) is included in satellite mission planning as an important part. A customer demand is finished only if the corresponding images are eventually downloaded. Due to the growing customer demands and the limited ground resources, SIDSP is an oversubscribed scheduling problem. In this paper, we investigate SIDSP with the case study of China’s commercial remote sensing satellite constellation (SuperView-1) and exploit the serial scheduling scheme for solving it. The idea is first determining a permutation of the downlink requests and then producing a schedule from the given ordered requests. A schedule generation algorithm (SGA) is proposed to assign the downlink time window for each scheduled request according to a given request permutation. A hybrid genetic algorithm (HGA) combined with neighborhood search is proposed to optimize the downlink request permutation with the purpose of maximizing the utility function. Experimental results on six groups of instances with different density demonstrate the effectiveness of the proposed approach.

scholarly journals Limited Search Space-Based Algorithm for Dual Resource Constrained Scheduling Problem with Multilevel Product Structure

2019 ◽  
Vol 9 (19) ◽  
pp. 4005 ◽  
Author(s):  
Geunho Yang ◽  
Byung Do Chung ◽  
Sang Jin Lee
Keyword(s):  
Genetic Algorithm ◽  
Job Shop ◽  
Hybrid Genetic Algorithm ◽  
Optimal Solution ◽  
Solution Space ◽  
Search Space ◽  
Product Structure ◽  
Neighborhood Search ◽  
Scheduling Problem ◽  
Resource Constrained

This study addresses the dual resource constrained flexible job shop scheduling problem (DRCFJSP) with a multilevel product structure. The DRCFJSP is a strong NP-hard problem, and an efficient algorithm is essential for DRCFJSP. In this study, we propose an algorithm for the DRCFJSP with a multilevel product structure to minimize the lateness, makespan, and deviation of the workload with preemptive priorities. To efficiently solve the problem within a limited time, the search space is limited based on the possible start and end time, and focus is placed on the intensification rather than diversification, which can help the algorithm spend more time to find an optimal solution in a reasonable solution space. The performance of the proposed algorithm is compared with those of a genetic algorithm and a hybrid genetic algorithm with variable neighborhood search. The numerical experiments demonstrate that the strategy limiting the search space is effective for large and complex problems.

Low-Carbon Job Shop Scheduling Problem with Discrete Genetic-Grey Wolf Optimization Algorithm

2020 ◽  
Vol 19 (01) ◽  
pp. 1-14
Author(s):  
Jiuchun Gu ◽  
Tianhua Jiang ◽  
Huiqi Zhu ◽  
Chao Zhang
Keyword(s):  
Optimization Algorithm ◽  
Job Shop ◽  
Job Shop Scheduling ◽  
Population Diversity ◽  
Neighborhood Search ◽  
Scheduling Problem ◽  
Low Carbon ◽  
Grey Wolf ◽  
Grey Wolf Optimization ◽  
Local Optima

The workshop scheduling has historically emphasized the production metrics without involving any environmental considerations. Low-carbon scheduling has attracted the attention of many researchers after the promotion of green manufacturing. In this paper, we investigate the low-carbon scheduling problem in a job shop environment. A mathematical model is first established with the objective to minimize the sum of energy-consumption cost and completion-time cost. A discrete genetic-grey wolf optimization algorithm (DGGWO) is developed to solve the problem in this study. According to the characteristics of the problem, a job-based encoding method is first employed. Then a heuristic approach and the random generation rule are combined to fulfill the population initialization. Based on the original GWO, a discrete individual updating method the crossover operation of the genetic algorithm is adopted to make the algorithm directly work in a discrete domain. Meanwhile, a mutation operator is adopted to enhance the population diversity and avoid the algorithm from getting trapped into the local optima. In addition, a variable neighborhood search is embedded to further improve the search ability. Finally, extensive simulations are conducted based on 43 benchmark instances. The experimental data demonstrate that the proposed algorithm can yield better results than the other published algorithms.

Scheduling Trucks in Multi-Door Cross Docking Systems: An Adaptive Genetic Algorithm with a Dispatching Rule

2015 ◽  
Vol 32 (03) ◽  
pp. 1550016 ◽  
Author(s):  
Byung Soo Kim ◽  
Cheol Min Joo
Keyword(s):  
Genetic Algorithms ◽  
Heuristic Algorithms ◽  
Optimal Solution ◽  
Operation Time ◽  
Adaptive Genetic Algorithm ◽  
Scheduling Problem ◽  
Cross Docking ◽  
Truck Scheduling ◽  
Total Operation Time ◽  
Management Concept

One of the most important operational management problems of a cross docking system is the truck scheduling problem. Cross docking is a logistics management concept in which products delivered to a distribution center by inbound trucks are immediately sorted out, routed and loaded into outbound trucks for delivery to customers. The truck scheduling problem in a multi-door cross docking system considered in this paper comprises the assignment of trucks to dock doors and the determination of docking sequences for all inbound and outbound trucks in order to minimize the total operation time. A mathematical model for optimal solution is derived, and the genetic algorithms (GAs) and the adaptive genetic algorithms (AGAs) as solution approaches with different types of chromosomes are proposed. The performance of the meta-heuristic algorithms are evaluated using randomly generated several examples.

scholarly journals Optimization for a Multi-Constraint Truck Appointment System Considering Morning and Evening Peak Congestion

2021 ◽  
Vol 13 (3) ◽  
pp. 1181
Author(s):  
Bowei Xu ◽  
Xiaoyan Liu ◽  
Yongsheng Yang ◽  
Junjun Li ◽  
Octavian Postolache
Keyword(s):  
Large Scale ◽  
Hybrid Genetic Algorithm ◽  
Urban Traffic ◽  
Container Terminals ◽  
Mixed Integer ◽  
Novel Approach ◽  
Appointment System ◽  
Truck Appointment System ◽  
Evening Peak ◽  
Operation Cost

Gate and yard congestion is a typical type of container port congestion, which prevents trucks from traveling freely and has become the bottleneck that constrains the port productivity. In addition, urban traffic increases the uncertainty of the truck arrival time and additional congestion costs. More and more container terminals are adopting a truck appointment system (TAS), which tries to manage the truck arrivals evenly all day long. Extending the existing research, this work considers morning and evening peak congestion and proposes a novel approach for multi-constraint TAS intended to serve both truck companies and container terminals. A Mixed Integer Nonlinear Programming (MINLP) based multi-constraint TAS model is formulated, which explicitly considers the appointment change cost, queuing cost, and morning and evening peak congestion cost. The aim of the proposed multi-constraint TAS model is to minimize the overall operation cost. The Lingo commercial software is used to solve the exact solutions for small and medium scale problems, and a hybrid genetic algorithm and simulated annealing (HGA-SA) is proposed to obtain the solutions for large-scale problems. Experimental results indicate that the proposed TAS can not only better serve truck companies and container terminals but also more effectively reduce their overall operation cost compared with the traditional TASs.

The Implementation Approach of LCCF Checklist in Development Control: Challenges for policymakers

2019 ◽  
Vol 4 (12) ◽  
Author(s):  
T B A
Keyword(s):  
Climate Change ◽  
Sustainable Development ◽  
Carbon Emissions ◽  
Local Authority ◽  
Survey Methods ◽  
Local Level ◽  
Control Process ◽  
Low Carbon ◽  
Local Authorities ◽  
Development Control

Global warming, climate change is now affecting the world. The effort of the leaders to achieving the sustainable development is from New Urban Agenda (NUA), Sustainable Development Goals (SDG’s) and local level is local authorities.  SDG’s goal number 13 takes urgent action to combat climate change and its impact also SDG’s number 11 to sustainable cities and communities. The gap of this paper  Different cities face different challenges and issues. Local authorities will play a significant role in undertaking policy initiatives to combat carbon emissions of the city. Low Carbon Cities (LCC) is to reduce carbon emissions in all human activities in cities.  The objective of this paper is by applying the LCCF Checklist in planning permission for sustainable development. The methodology of this research is a mixed-method, namely quantitative and qualitative approach. The survey methods are by interview, questionnaire, and observation. Town planners are the subject matter expert in managing the planning permission submission for the development control of their areas. Descriptive statistical analysis will be used to show the willingness of the stakeholders, namely the developers and planning consultants in implementing of the LCCF. The contribution of this research will gauge readiness at the local authorities level. The findings of the LCCF checklist are identified as important in planning permission into the development control process. Surprisingly, that challenges and issues exist in multifaceted policy implementation the LCCF Checklist in a local authority. Finally based on Subang Jaya Municipal Councils, the existing approach in the application of the LCCF Checklist in the development control process will be useful for development control in a local authority towards sustainable development.  

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