scholarly journals The Location Inventory Routing Optimization Model and Algorithm for the Islands Shipping Network

2021 ◽  
Author(s):  
Di Wu ◽  
Nuo Wang
Keyword(s):  
Genetic Algorithm ◽  
Sensitivity Analysis ◽  
Hybrid Genetic Algorithm ◽  
Construction Cost ◽  
Inventory Routing ◽  
Routing Problem ◽  
Hub And Spoke ◽  
Total Cost ◽  
Routing Optimization ◽  
Practical Information

Abstract This paper studies a hub-and-spoke shipping network of islands and integrates a maritime location inventory routing problem (MLIRP) for the islands shipping network. By determining a series of decisions including the location of the hub islands, the number of shipping routes, the schedule of every route, the running mode of every route, the ship size, the wharf scale and the inventory capacity, the objective of the paper is to minimize the total cost of the islands shipping network. For solving the integrated MLIRP model, a hybrid genetic algorithm based on the stepwise configuration (SC-GA) is presented. Finally, instances are put forward to evaluate the performance of the algorithm. The results of sensitivity analysis show that the wharf construction cost affects the total costs the most, so more attention should be paid to it when making decisions. This paper can provide theoretical and practical information to design and optimize an islands shipping network.

scholarly journals Green Inventory Routing Problem using Hybrid Genetic Algorithm

2021 ◽  
Vol 6 (4) ◽  
pp. 10-19
Author(s):  
Huda Zuhrah Ab Halim ◽  
Nureffa Natasha Mohd Azliana ◽  
Nuridawati Baharom ◽  
Nur Fatihah Fauzi ◽  
Nurizatul Syarfinas Ahmad Bakhtiar ◽  
...  
Keyword(s):  
Carbon Dioxide ◽  
Genetic Algorithm ◽  
Supply Chain ◽  
Fuel Consumption ◽  
Hybrid Genetic Algorithm ◽  
Inventory Routing ◽  
Routing Problem ◽  
Total Cost ◽  
Inventory Routing Problem ◽  
Consumption Cost

Carbon dioxide (CO2) is known as one of the largest sources of global warming. One of the ways to curb CO2 emissions is by considering the environmental aspect in the supply chain management. This paper analyses the influence of carbon emissions on the Inventory Routing Problem (IRP). The IRP network consists of a depot, an assembly plant and multiple suppliers. The deterministic demands vary and are determined by the assembly plant. Fixed transportation cost, fuel consumption cost and inventory holding cost are used to evaluate the system’s total cost in which fuel consumption cost is determined by fuel consumption rate, distance, and fuel price. Backordering and split pick-up are not allowed. The main purpose of this study is to analyze the distribution network especially the overall costs of the supply chain by considering the CO2 emissions as well. The problem is known as Green Inventory Routing Problem (GIRP). The mixed-integer linear programming of this problem is adopted from Cheng et al. wherein this study a different Hybrid Genetic Algorithm is proposed at mutation operator. As predicted, GIRP has a higher total cost as it considered fuel consumption cost together with the transportation and inventory costs. The results showed the algorithm led to different sequences of routings considering the carbon dioxide emission in the objective function.

Enterprise distribution routing optimization with soft time windows based on genetic algorithm

2021 ◽  
pp. 1-11
Author(s):  
Kaixian Gao ◽  
Guohua Yang ◽  
Xiaobo Sun
Keyword(s):  
Genetic Algorithm ◽  
Customer Satisfaction ◽  
Optimization Problems ◽  
Rapid Development ◽  
Time Windows ◽  
Theory And Practice ◽  
Routing Problem ◽  
Logistics Industry ◽  
Routing Optimization ◽  
A Company

With the rapid development of the logistics industry, the demand of customer become higher and higher. The timeliness of distribution becomes one of the important factors that directly affect the profit and customer satisfaction of the enterprise. If the distribution route is planned rationally, the cost can be greatly reduced and the customer satisfaction can be improved. Aiming at the routing problem of A company’s vehicle distribution link, we establish mathematical models based on theory and practice. According to the characteristics of the model, genetic algorithm is selected as the algorithm of path optimization. At the same time, we simulate the actual situation of a company, and use genetic algorithm to plan the calculus. By contrast, the genetic algorithm suitable for solving complex optimization problems, the practicability of genetic algorithm in this design is highlighted. It solves the problem of unreasonable transportation of A company, so as to get faster efficiency and lower cost.

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