System to Solve the Inventory Routing Problem with Stochastic Demand and Time Window

2018 ◽  
Author(s):  
Pedro Yuri A. L. Alves ◽  
Karina Valdivia Delgado ◽  
Alexandre da Silva Freire ◽  
Valdinei Freire da Silva
Keyword(s):  
Time Window ◽  
Stochastic Demand ◽  
Inventory Routing ◽  
Routing Problem ◽  
Inventory Routing Problem

scholarly journals Research on inventory path optimization of VMI large logistics enterprises based on ant colony algorithm

2021 ◽  
pp. 1-11
Author(s):  
Yaoyan Wang
Keyword(s):  
Ant Colony Algorithm ◽  
Time Window ◽  
Ant Colony ◽  
Path Optimization ◽  
Inventory Routing ◽  
Logistics System ◽  
Routing Problem ◽  
Inventory Routing Problem ◽  
Logistics Enterprises ◽  
Improved Ant Colony Algorithm

Based on the idea of vendor management (VMI) inventory, this paper focuses on the integration and optimization of transportation and inventory control in large-scale logistics system, so as to minimize the total cost of the logistics system. Aiming at the inventory path optimization of VMI large logistics enterprises, based on ant colony algorithm, an improved ant colony algorithm, namely ant colony system algorithm, is designed to solve the model. The algorithm model combines deterministic selection and random selection to obtain a comprehensive probability, and combines local and global pheromone updating. In this paper, we study a two-level supply chain system with multiple customers from one supplier and inventory routing problem. According to the characteristics of inventory routing problem, a single cycle inventory path optimization model with time window constraint based on stochastic demand is established. The goal is to minimize the total system cost, including inventory cost of downstream customers, system transportation cost and penalty cost for not meeting the time window. According to the characteristics of the model, the ant colony algorithm is selected as the optimization method, and the improved ant colony algorithm is designed to solve the example, and the feasibility of the algorithm and model is verified.

scholarly journals Integrated Inventory Routing Problem with Quality Time Windows and Loading Cost for Deteriorating Items under Discrete Time

2014 ◽  
Vol 2014 ◽  
pp. 1-14 ◽  
Author(s):  
Tao Jia ◽  
Xiaofan Li ◽  
Nengmin Wang ◽  
Ran Li
Keyword(s):  
Discrete Time ◽  
Production Scheduling ◽  
Time Window ◽  
Mixed Integer ◽  
Time Interval ◽  
Second Phase ◽  
Inventory Routing ◽  
Routing Problem ◽  
Inventory Routing Problem ◽  
Integrated Inventory

We investigate an integrated inventory routing problem (IRP) in which one supplier with limited production capacity distributes a single item to a set of retailers using homogeneous vehicles. In the objective function we consider a loading cost which is often neglected in previous research. Considering the deterioration in the products, we set a soft time window during the transportation stage and a hard time window during the sales stage, and to prevent jams and waiting cost, the time interval of two successive vehicles returning to the supplier’s facilities is required not to be overly short. Combining all of these factors, a two-echelon supply chain mixed integer programming model under discrete time is proposed, and a two-phase algorithm is developed. The first phase uses tabu search to obtain the retailers’ ordering matrix. The second phase is to generate production scheduling and distribution routing, adopting a saving algorithm and a neighbourhood search, respectively. Computational experiments are conducted to illustrate the effectiveness of the proposed model and algorithm.

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