scholarly journals Green Logistics Location-Routing Optimization Solution Based on Improved GA A1gorithm considering Low-Carbon and Environmental Protection

2021 ◽  
Vol 2021 ◽  
pp. 1-16
Author(s):  
Anqing Zhu ◽  
Youyun Wen
Keyword(s):  
Environmental Protection ◽  
Optimization Problem ◽  
Time Window ◽  
Cost Minimization ◽  
Low Carbon ◽  
Improved Genetic Algorithm ◽  
Green Logistics ◽  
Routing Optimization ◽  
Location Routing ◽  
Ga Algorithm

This paper proposes a green logistics location-routing optimization problem based on improved genetic algorithm (GA) from the perspective of low-carbon and environmental protection. First, considering the cost factor, time window, deterioration rate of agricultural products, inventory and distribution capacity, carbon trading mechanism, and other factors, and with the total cost minimization as the optimization goal, a low-carbon and environmental protection logistics location-routing optimization model is constructed. Then, the adaptive operator and cataclysm operator are introduced to improve the GA algorithm, which can adjust crossover and mutation probability according to the needs, reducing the influence of parameters and running time. Furthermore, the improved GA algorithm is used to solve the location-routing optimization problem in green logistics, so as to obtain a low-carbon, economical, and efficient distribution path. Finally, perform experimental analysis of the proposed method using the relevant data of U company. The results show that the total distribution cost is 6771.3 yuan, which meets the design requirements of economy and environmental protection.

scholarly journals MULTI-OBJECTIVE DISTRIBUTION ROUTING OPTIMIZATION WITH TIME WINDOW BASED ON IMPROVED GENETIC ALGORITHM

2018 ◽  
Vol 48 (3) ◽  
pp. 151-156
Author(s):  
S. WU ◽  
C. CHEN
Keyword(s):  
Genetic Algorithm ◽  
Time Window ◽  
Time Windows ◽  
Optimal Solution ◽  
Transportation Cost ◽  
Population Diversity ◽  
Improved Genetic Algorithm ◽  
Routing Problem ◽  
Logistics Distribution ◽  
Routing Optimization

In order to solve the shortcomings of the traditional genetic algorithm in solving the problem of logistics distribution path, a modified genetic algorithm is proposed to solve the Vehicle Routing Problem with Time Windows (VRPTW) under the condition of vehicle load and time window. In the crossover process, the best genes can be preserved to reduce the inferior individuals resulting from the crossover, thus improving the convergence speed of the algorithm. A mutation operation is designed to ensure the population diversity of the algorithm, reduce the generation of infeasible solutions, and improve the global search ability of the algorithm. The algorithm is implemented on Matlab 2016a. The example shows that the improved genetic algorithm reduces the transportation cost by about 10% compared with the traditional genetic algorithm and can jump out of the local convergence and obtain the optimal solution, thus providing a more reasonable vehicle route.

scholarly journals Implementation of Green Logistics Management Strategy in Low Carbon Economy

2019 ◽  
Vol 3 (4) ◽  
pp. 64
Author(s):  
Xiuli Li
Keyword(s):  
Environmental Protection ◽  
Management Strategy ◽  
Logistics Management ◽  
Low Carbon ◽  
Green Logistics ◽  
Logistics Industry ◽  
Low Carbon Economy ◽  
Green Development ◽  
Operation And Management ◽  
Carbon Economy

<p>At present, it is of great significance for the development of China's logistics industry to advocate low-carbon economy worldwide, integrate green development and environmental protection into the operation and management of the logistics industry and embody green environmental protection in the formulation of logistics management-related strategies. Based on the principles of low-carbon economy and green logistics, this paper discusses the ways to promote the development of green logistics under the environment of low-carbon economy.</p>

Parcel delivery cost minimization with time window constraints using trucks and drones

Networks ◽  
2021 ◽  
Author(s):  
Marc‐Antoine Coindreau ◽  
Olivier Gallay ◽  
Nicolas Zufferey
Keyword(s):  
Time Window ◽  
Cost Minimization ◽  
Delivery Cost ◽  
Time Window Constraints

Schedule-Constrained Demand Management in Two-Region Urban Networks

2021 ◽  
Author(s):  
Sakitha Kumarage ◽  
Mehmet Yildirimoglu ◽  
Mohsen Ramezani ◽  
Zuduo Zheng
Keyword(s):  
Nonlinear Optimization ◽  
Optimization Problem ◽  
Time Window ◽  
Demand Management ◽  
Urban Traffic ◽  
Fundamental Diagram ◽  
Constrained System ◽  
Nonlinear Optimization Problem ◽  
Management Platform ◽  
User Compliance

Demand management aiming to optimize system cost while ensuring user compliance in an urban traffic network is a challenging task. This paper introduces a cooperative demand redistribution strategy to optimize network performance through the retiming of departure times within a limited time window. The proposed model minimizes the total time spent in a two-region urban network by incurring minimal disruption to travelers’ departure schedules. Two traffic models based on the macroscopic fundamental diagram (MFD) are jointly implemented to redistribute demand and analyze travelers’ reaction. First, we establish equilibrium conditions via a day-to-day assignment process, which allows travelers to find their preferred departure times. The trip-based MFD model that incorporates individual traveler attributes is implemented in the day-to-day assignment, and it is conjugated with a network-level detour ratio model to incorporate the effect of congestion in individual traveler route choice. This allows us to consider travelers with individual preferences on departure times influenced by desired arrival times, trip lengths, and earliness and lateness costs. Second, we develop a nonlinear optimization problem to minimize the total time spent considering both observed and unobserved demand—that is, travelers opting in and out of the demand management platform. The accumulation-based MFD model that builds on aggregated system representation is implemented as part of the constraints in the nonlinear optimization problem. The results confirm the resourcefulness of the model to address complex two-region traffic dynamics and to increase overall performance by reaching a constrained system optimum scenario while ensuring the applicability at both full and partial user compliance conditions.

Research and Design of Energy-Saving and Environmental-Protection Full Evaporative Air Cooler

2013 ◽  
Vol 368-370 ◽  
pp. 400-410
Author(s):  
Li Xin Shang ◽  
Chuan Yi Zhou ◽  
Yun Tao Jing
Keyword(s):  
Energy Conservation ◽  
Automatic Control ◽  
Environmental Protection ◽  
Main Body ◽  
Low Carbon ◽  
Low Carbon Economy ◽  
Air Cooler ◽  
History Of ◽  
Research And Design ◽  
Carbon Economy

Our country is in a low carbon economy development period, this paper described the whole evaporative air cooler is based on energy conservation and environmental protection thinking of development, this paper described the development history of air cooler in energy conservation and environmental protection, the main body of the thinking of equipment design and each index assessment, in a large number of experimental data are put forward on the basis of the concept of "full evaporation", according to the requirements of the indicators and process requirements of equipment parts for detailed design of equipment, automatic control design, form the mechanical and electrical integration, energy conservation and environmental protection, automatic control, full evaporative air cooler and heat exchange equipment.

scholarly journals Model and Algorithm of Two-Stage Distribution Location Routing with Hard Time Window for City Cold-Chain Logistics

2020 ◽  
Vol 10 (7) ◽  
pp. 2564
Author(s):  
Liying Yan ◽  
Manel Grifoll ◽  
Pengjun Zheng
Keyword(s):  
Time Window ◽  
Hybrid Genetic Algorithm ◽  
Distribution Networks ◽  
Cold Chain ◽  
Two Stage ◽  
Logistics Network ◽  
Stage Distribution ◽  
Hard Time ◽  
Location Routing ◽  
Logistics Enterprises

Taking cold-chain logistics as the research background and combining with the overall optimisation of logistics distribution networks, we develop two-stage distribution location-routing model with the minimum total cost as the objective function and varying vehicle capacity in different delivery stages. A hybrid genetic algorithm is designed based on coupling and collaboration of the two-stage routing and transfer stations. The validity and feasibility of the model and algorithm are verified by conducting a randomly generated test. The optimal solutions for different objective functions of two-stage distribution location-routing are compared and analysed. Results turn out that for different distribution objectives, different distribution schemes should be employed. Finally, we compare the two-stage distribution location-routing to single-stage vehicle routing problems. It is found that a two-stage distribution location-routing system is feasible and effective for the cold-chain logistics network, and can decrease distribution cost for cold-chain logistics enterprises.

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