Multi-Cast Ant Colony System for the Bus Routing Problem

2003 ◽  
pp. 91-125 ◽  
Author(s):  
Urszula Boryczka ◽  
Mariusz Boryczka
Keyword(s):  
Ant Colony ◽  
Ant Colony System ◽  
Routing Problem ◽  
Bus Routing

scholarly journals The Fourth-Party Logistics Routing Problem Using Ant Colony System-Improved Grey Wolf Optimization

2020 ◽  
Vol 2020 ◽  
pp. 1-15
Author(s):  
Fuqiang Lu ◽  
Wenjing Feng ◽  
Mengying Gao ◽  
Hualing Bi ◽  
Suxin Wang
Keyword(s):  
Ant Colony ◽  
Third Party ◽  
Destination Node ◽  
Problem Analysis ◽  
Ant Colony System ◽  
Grey Wolf ◽  
Grey Wolf Optimization ◽  
Routing Problem ◽  
Initial Node ◽  
Fourth Party Logistics

The fourth-party logistics routing problem (4PLRP) is an important issue in the operation of fourth-party logistics (4PL). In this paper, the study of fourth-party logistics (4PL) path optimization considers that more third-party logistics (3PL) undertake transportation tasks. Under the condition that the 3PL transportation time, transportation cost, node transit time, and transit cost are uncertain, 4PL provides customers with a set of transportation solutions to transport transportation tasks from the initial node to the destination node according to the customer’s risk aversion preference. The transportation scheme not only meets the customer’s time and cost requirements but also meets the carrying capacity and reputation constraints of 3PL. Between the two nodes, one or more 3PLs will undertake the transportation task. The customer’s risk preference will be measured by the ratio utility theory (RUT). An ant colony system-improved grey wolf optimization (ACS-IGWO) is designed to solve the model, and the grey wolf optimization (GWO) is improved by the convergence factor and the proportional weight. Problem analysis is conducted through simulation experiments.

The Application of a Improved Hybrid Ant Colony Algorithm in Vehicle Routing Optimization Problem

2014 ◽  
Vol 556-562 ◽  
pp. 4693-4696
Author(s):  
Yue Li Li ◽  
Ai Hua Ren
Keyword(s):  
Vehicle Routing ◽  
Vehicle Routing Problem ◽  
Ant Colony Algorithm ◽  
Ant Colony ◽  
Ant Colony System ◽  
Routing Problem ◽  
Logistics Industry ◽  
Routing Optimization ◽  
Constrained Vehicle Routing ◽  
Capacity Constrained

With the development of the market economy, the logistics industry has been developed rapidly.It is easy to understand that good vehicle travel path planning has very important significance in the logistics company,especially in the general production enterprises. This paper mainly studies the microcosmic traffic system in the type of vehicle routing problems: capacity-constrained vehicle routing problem. We demonstrate the use of Ant Colony System (ACS) to solve the capacitated vehicle routing problem, treated as nodes in a spatial network. For the networks where the nodes are concentrated, the use of hybrid heuristic optimization can greatly improve the efficiency of the solution. The algorithm produces high-quality solutions for the capacity-constrained vehicle routing problem.

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