scholarly journals The Tractor and Semitrailer Routing Considering Carbon Dioxide Emissions

2013 ◽  
Vol 2013 ◽  
pp. 1-12 ◽  
Author(s):  
Hongqi Li ◽  
Yanran Li ◽  
Qiuhong Zhao ◽  
Yue Lu ◽  
Qiang Song
Keyword(s):  
Carbon Dioxide ◽  
Simulated Annealing ◽  
Integer Programming ◽  
Heuristic Algorithm ◽  
Carbon Dioxide Emissions ◽  
Programming Model ◽  
Small Scale ◽  
Scale Problem ◽  
Routing Problem ◽  
Second Stage

The incorporation of the minimization of carbon dioxide (CO2) emissions in the VRP is important to logistics companies. The paper deals with the tractor and semitrailer routing problem with full truckload between any two depots of the network; an integer programming model with the objective of minimizing CO2emissions per ton-kilometer is proposed. A two-stage approach with the same core steps of the simulated annealing (SA) in both stages is designed. The number of tractors is provided in the first stage and the CO2emissions per ton-kilometer are then optimized in the second stage. Computational experiments on small-scale randomly generated instances supported the feasibility and validity of the heuristic algorithm. To a practical-scale problem, the SA algorithm can provide advice on the number of tractors, the routes, and the location of the central depot to realize CO2emissions decrease.

scholarly journals Modeling the Multicommodity Multimodal Routing Problem with Schedule-Based Services and Carbon Dioxide Emission Costs

2015 ◽  
Vol 2015 ◽  
pp. 1-21 ◽  
Author(s):  
Yan Sun ◽  
Maoxiang Lang
Keyword(s):  
Carbon Dioxide ◽  
Carbon Dioxide Emissions ◽  
Transportation Network ◽  
Linearization Method ◽  
Mixed Integer ◽  
Multicommodity Flow ◽  
Routing Problem ◽  
Multimodal Transportation ◽  
Proposed Model ◽  
Freight Routing

We explore a freight routing problem wherein the aim is to assign optimal routes to move commodities through a multimodal transportation network. This problem belongs to the operational level of service network planning. The following formulation characteristics will be comprehensively considered: (1) multicommodity flow routing; (2) a capacitated multimodal transportation network with schedule-based rail services and time-flexible road services; (3) carbon dioxide emissions consideration; and (4) a generalized costs optimum oriented to customer demands. The specific planning of freight routing is thus defined as a capacitated time-sensitive multicommodity multimodal generalized shortest path problem. To solve this problem systematically, we first establish a node-arc-based mixed integer nonlinear programming model that combines the above formulation characteristics in a comprehensive manner. Then, we develop a linearization method to transform the proposed model into a linear one. Finally, a computational experiment from the Chinese inland container export business is presented to demonstrate the feasibility of the model and linearization method. The computational results indicate that implementing the proposed model and linearization method in the mathematical programming software Lingo can effectively solve the large-scale practical multicommodity multimodal transportation routing problem.

scholarly journals A Two-Stage Simulated Annealing Algorithm for the Many-to-Many Milk-Run Routing Problem with Pipeline Inventory Cost

2015 ◽  
Vol 2015 ◽  
pp. 1-22 ◽  
Author(s):  
Yu Lin ◽  
Zheyong Bian ◽  
Shujing Sun ◽  
Tianyi Xu
Keyword(s):  
Simulated Annealing ◽  
Heuristic Algorithm ◽  
Simulated Annealing Algorithm ◽  
Greedy Heuristic ◽  
Two Stage ◽  
Satisfactory Solution ◽  
Routing Problem ◽  
Annealing Algorithm ◽  
The Many ◽  
Milk Run

In recent years, logistics systems with multiple suppliers and plants in neighboring regions have been flourishing worldwide. However, high logistics costs remain a problem for such systems due to lack of information sharing and cooperation. This paper proposes an extended mathematical model that minimizes transportation and pipeline inventory costs via the many-to-many Milk-run routing mode. Because the problem is NP hard, a two-stage heuristic algorithm is developed by comprehensively considering its characteristics. More specifically, an initial satisfactory solution is generated in the first stage through a greedy heuristic algorithm to minimize the total number of vehicle service nodes and the best insertion heuristic algorithm to determine each vehicle’s route. Then, a simulated annealing algorithm (SA) with limited search scope is used to improve the initial satisfactory solution. Thirty numerical examples are employed to test the proposed algorithms. The experiment results demonstrate the effectiveness of this algorithm. Further, the superiority of the many-to-many transportation mode over other modes is demonstrated via two case studies.

scholarly journals Multidepot Heterogeneous Vehicle Routing Problem for a Variety of Hazardous Materials with Risk Analysis

2020 ◽  
Vol 2020 ◽  
pp. 1-11
Author(s):  
Bochen Wang ◽  
Qiyuan Qian ◽  
Zheyi Tan ◽  
Peng Zhang ◽  
Aizhi Wu ◽  
...  
Keyword(s):  
Risk Analysis ◽  
Vehicle Routing ◽  
Vehicle Routing Problem ◽  
Large Scale ◽  
Programming Model ◽  
Hazardous Materials ◽  
Mixed Integer ◽  
Small Scale ◽  
Routing Problem ◽  
Heterogeneous Vehicle Routing Problem

This study investigates a multidepot heterogeneous vehicle routing problem for a variety of hazardous materials with risk analysis, which is a practical problem in the actual industrial field. The objective of the problem is to design a series of routes that minimize the total cost composed of transportation cost, risk cost, and overtime work cost. Comprehensive consideration of factors such as transportation costs, multiple depots, heterogeneous vehicles, risks, and multiple accident scenarios is involved in our study. The problem is defined as a mixed integer programming model. A bidirectional tuning heuristic algorithm and particle swarm optimization algorithm are developed to solve the problem of different scales of instances. Computational results are competitive such that our algorithm can obtain effective results in small-scale instances and show great efficiency in large-scale instances with 70 customers, 30 vehicles, and 3 types of hazardous materials.

scholarly journals Flow Merging and Hub Route Optimization in Collaborative Transportation

2014 ◽  
Vol 2014 ◽  
pp. 1-8 ◽  
Author(s):  
Kerui Weng ◽  
Zi-hao Xu
Keyword(s):  
Integer Programming ◽  
Lagrangian Relaxation ◽  
Benders Decomposition ◽  
Programming Model ◽  
Route Optimization ◽  
Mixed Integer ◽  
Routing Problem ◽  
Fixed Charges ◽  
Postal Services ◽  
Cost Discount

This paper studies the optimal hub routing problem of merged tasks in collaborative transportation. This problem allows all carriers’ transportation tasks to reach the destinations optionally passing through 0, 1, or 2 hubs within limited distance, while a cost discount on arcs in the hub route could be acquired after paying fixed charges. The problem arises in the application of logistics, postal services, airline transportation, and so forth. We formulate the problem as a mixed-integer programming model, and provide two heuristic approaches, respectively, based on Lagrangian relaxation and Benders decomposition. Computational experiments show that the algorithms work well.

A Hybrid Meta-Heuristic Algorithm for Vehicle Routing Problem with Time Windows

2015 ◽  
Vol 24 (06) ◽  
pp. 1550021 ◽  
Author(s):  
Esam Taha Yassen ◽  
Masri Ayob ◽  
Mohd Zakree Ahmad Nazri ◽  
Nasser R. Sabar
Keyword(s):  
Simulated Annealing ◽  
Vehicle Routing ◽  
Heuristic Algorithm ◽  
Vehicle Routing Problem ◽  
Optimization Problems ◽  
Search Algorithm ◽  
Time Windows ◽  
Harmony Search ◽  
Harmony Search Algorithm ◽  
Routing Problem

Harmony search algorithm, which simulates the musical improvisation process in seeking agreeable harmony, is a population based meta-heuristics algorithm for solving optimization problems. Although it has been successfully applied on various optimization problems; it suffers the slow convergence problem, which greatly hinders its applicability for getting good quality solution. Therefore, in this work, we propose a hybrid meta-heuristic algorithm that hybridizes a harmony search with simulated annealing for the purpose of improving the performance of harmony search algorithm. Harmony search algorithm is used to explore the search spaces. Whilst, simulated annealing algorithm is used inside the harmony search algorithm to exploit the search space and further improve the solutions that are generated by harmony search algorithm. The performance of the proposed algorithm is tested using the Solomon's Vehicle Routing Problem with Time Windows (VRPTW) benchmark. Numerical results demonstrate that the hybrid approach is better than the harmony search without simulated annealing and the hybrid also proves itself to be more competent (if not better on some instances) when compared to other approaches in the literature.

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