Low-carbon VRP for cold chain logistics considering real-time traffic conditions in the road network

PurposeThis paper studies low-carbon vehicle routing problem (VRP) for cold chain logistics with the consideration of the complexity of the road network and the time-varying traffic conditions, and then a low-carbon cold chain logistics routing optimization model was proposed. The purpose of this paper is to minimize the carbon emission and distribution cost, which includes vehicle operation cost, product freshness cost, quality loss cost, penalty cost and transportation cost.Design/methodology/approachThis study proposed a mathematical optimization model, considering the distribution cost and carbon emission. The improved Nondominated Sorting Genetic Algorithm II algorithm was used to solve the model to obtain the Pareto frontal solution set.FindingsThe result of this study showed that this model can more accurately assess distribution costs and carbon emissions than those do not take real-time traffic conditions in the actual road network into account and provided guidance for cold chain logistics companies to choose a distribution strategy and for the government to develop a carbon tax.Research limitations/implicationsThere are some limitations in the proposed model. This study assumes that there are only one distribution and a single type of vehicle.Originality/valueExisting research on low-carbon VRP for cold chain logistics ignores the complexity of the road network and the time-varying traffic conditions, resulting in nonmeaningful planned distribution routes and furthermore low carbon cannot be discussed. This study takes the complexity of the road network and the time-varying traffic conditions into account, describing the distribution costs and carbon emissions accurately and providing the necessary prerequisites for achieving low carbon.

Optimizing Rice Distribution Model Using Linear Programming at West Java Bulog

Good distribution network management is a very important competitive advantage for a company. West Java Bulog is the representative of the government in distributing and distributing rice, which is a staple food commodity for the Indonesian people in general, of course, must pay attention to the optimal distribution pattern. In carrying out its operational processes, West Java Bulog will be assisted by 7 regional subdivisions spread throughout the West Java region who will handle rice in their respective working areas. This study aims to determine the planning path and the optimum amount of rice distribution from the West Java Bulog to districts and cities that can minimize distribution costs so that the costs incurred will reach the lowest point using the Linear Programming method. The analysis of this research was assisted by LINDO Software version 7.0 for Windows 10.0. From the results of this study, the optimization of rice distribution at the West Java Bulog, with the optimum total distribution cost of USD 124,272.

Optimization of Rice Distribution Using a Linear Programming Model at Perum Bulog, West Java Regional Division, Indonesia

Good distribution network management is a very important competitive advantage for a company. The distribution that is not right with the wrong time will also have a big impact on all aspects, especially company profits. The exact number and timing are crucial points in the distribution. The distribution and transportation system must be designed optimally so that the minimum cost is obtained. Perum Bulog, West Java Regional Division, is the government's representative in distributing rice evenly and distributing rice, which is a staple food commodity for Indonesian people in general. Of course, it must pay attention to optimal distribution patterns. In carrying out the operational process, the West Java Regional Division of Perum Bulog will be assisted by 7 Regional Sub-Divisions scattered throughout the West Java region who will handle rice in their respective working areas. This study aims to determine the planning path and the optimum amount of rice distribution from the West Java Regional Division to districts and cities that can minimize distribution costs so that the costs incurred will reach their lowest point using the Linear Programming method. The analysis of this research was assisted by the LINDO software version 7.0 for Windows 10.0. From the results of this research, the optimization of rice distribution at Perum Bulog Divre West Java, with the optimum total distribution cost is IDR 6,374,025 360.

Socio-economic analysis of Baroda branch canal of Som Kamla Amba irrigation project, Dungarpur, Rajasthan

Irrigation system development results in improvements of farmers' economy, followed by livelihood sustainability, standard of living and social attitude. Present analysis focused on socio-economic status of farming families in the command area of Baroda Branch Canal of Som Kamla Amba Irrigation Project. The study considered survey sampling of 10 per cent beneficiaries in the Baroda branch canal command which consisted 150 farming families having 787 persons in numbers. The socio-economic indicators viz., the family structures, employment pattern, education status, livestock ownership, farm asset distribution, cost of cultivation, and cost of returns were analysed. Results indicated that education and living standards are of farmers was low which may be one of the reasons for not adoption of newly farming technologies. Cost of cultivation per hectare for wheat, barley, gram, and mustard crops were found as Rs. 28,503.00, Rs. 26,727.00, Rs. 21,184.00 and Rs. 21,697.00, respectively and net benefits per hectare obtained from these crops were Rs. 13,297, Rs. 13,023, Rs. 14,416 and Rs. 18,303, respectively. The pattern of ownership of livestock showed that the average number of cows in the command area was about 1.97 per family. The productivity in the area is average due to low inputs use.

Algorithms for Picking and Distribution of Online Orders in New Retail Enterprises

This paper studies joint algorithms of order picking and distribution in new retail enterprises. The problem will consider many factors, such as the type of goods, picking time, batch capacity of distribution, distribution time, and distribution cost. First of all, the research problems are summarized as mathematical programming problems. Then, a genetic algorithm and comparison algorithms are proposed. Finally, the rationality of the model and the effectiveness of the algorithms are verified by computational experiments, and management enlightenments are revealed.

Research on Logistics Distribution Path Planning Based on Genetic Algorithm

In this paper, SF express company Jinzhou Guta District Pinganli business point as an example, to investigate its distribution, statistical analysis of the survey results, summed up the problems in logistics and distribution. Through the systematic study of the problem, a planning model with time window and with the objective of minimizing the total cost of distribution is established. At the same time, an intelligent algorithm for distribution path optimization - Genetic Algorithm (GA) is designed. Genetic algorithm is used to design chromosome coding methods and genetic operators for solving the planning model with the objective of minimizing the total cost of distribution. Finally, the simulation experiment is carried out. MATLAB software is used to solve the distribution route and the total driving distance of vehicles, and the distribution route with the goal of minimizing the total distribution cost is obtained.

An Improved Genetic Algorithm for the Optimal Distribution of Fresh Products under Uncertain Demand

There are increasing challenges for optimally distributing fresh products while adequately considering the uncertain demand of customers and maintaining the freshness of products. Taking the nature of fresh products and the characteristics of urban logistics systems into consideration, this paper proposes an improved genetic algorithm for effectively solving this problem in a computationally efficient manner. Such an algorithm can adequately account for the uncertain demand of customers to select the optimal distribution route to ensure the freshness of the product while minimizing the total distribution cost. Iterative optimization procedures are utilized for determining the optimal route by reducing the complexity of the computation in the search for an optimal solution. An illustrative example is presented that shows the improved algorithm is more effective with respect to the distribution cost, the distribution efficiency, and the distribution system’s reliability in optimally distributing fresh products.

Optimization of Distribution Path considering Cost and Customer Satisfaction under New Retail Modes

One of the top issues in logistics management and related research is to establish an effective distribution system that is adaptive to new retail and capable of lowering the cost of logistics while enhancing consumer satisfaction. Aimed at reversing the weak points of current logistics distribution patterns, a dual-objective bipolar model with optimal logistics cost and consumer satisfaction by restraining distribution time and load is tested in this paper to figure out the proper nodes and vehicle routes. Data from general and front warehouses of PuPu mall, a Fuzhou-based online retail enterprise, are made into a case study. Moreover, the immune algorithm and genetic algorithm are adopted to achieve the model solution. It is found that the immune algorithm is more efficient than the genetic algorithm in searching solutions, thus having better adaptivity and effectiveness, and also that the type of distribution vehicle plays a significant role in determining the total distribution cost.

An optimization model of cross-docking scheduling of cold chain logistics based on fuzzy time window

In order to improve the distribution efficiency of cold chain logistics and reduce the distribution cost, an optimization model of cross-docking scheduling of cold chain logistics based on fuzzy time window is constructed. According to the complexity of cold chain logistics network, a multi-objective optimization model of cross-docking scheduling of cold chain logistics vehicle routing with fuzzy time window is established. In order to ensure the lowest total cost of cold chain logistics distribution and improve the overall customer satisfaction with service time, the Drosophila optimization algorithm is used to solve the model to obtain the optimal vehicle routing of cross-docking scheduling optimization of cold chain logistics. The simulation test results show that: after the application of the model, the cold chain logistics distribution time is significantly shortened, the distribution cost is significantly reduced, the damage cost is reduced, the carbon emission of vehicles is reduced, and the economic and low-carbon benefits are significantly improved, which can be used as an effective tool to solve the cross-docking scheduling optimization problem of cold chain logistics.