TY  - JOUR
T1  - A Genetic Algorithm for Optimizing the Amount of Emissions of Greenhouse GAZ for Capacitated Vehicle Routing Problem in Green Transportation
AU - El Idrissi Adiba, El Bouzekri AU - Ahmed, El Hilali Alaoui AU - Youssef, Benadada 
JO  - International Journal of Soft Computing
VL  - 8
IS  - 6
SP  - 406
EP  - 415
PY  - 2013
DA  - 2001/08/19
SN  - 1816-9503
DO  - ijscomp.2013.406.415
UR  - https://makhillpublications.co/view-article.php?doi=ijscomp.2013.406.415
KW  - Environment
KW  -green transportation
KW  -greenhouse emissions
KW  -capacitated vehicle routing problem
KW  -emission matrix
KW  -genetic algorithm
KW  -freight transport
AB  - In today’s 
  highly competitive environment, green transportation issues are gaining interest 
  from theoretical, political and social perspectives. Freight road transport 
  that is one important aspect of environmentally responsible logistics is discussed 
  in depth. The activity of transport causes a high rate of negative effects on 
  the environment as pollutants emission (greenhouse gas). The immediate consequence 
  of this effect is depletion of ozone layer and climate change that is the reason 
  why researchers must been reducing the emissions from the sector. Nevertheless, 
  the classical Capacitated Vehicle Routing Problem (CVRP) with the objective 
  of minimizing the greenhouse gas especially the carbon dioxide (CO<SUB>2</SUB>), 
  states for the problem of finding routes for vehicles to serve a set of customers 
  while minimizing the total traveled distance and the CO<SUB>2</SUB> emissions. 
  Researchers present in this study the technique employed to estimate de CO<SUB>2</SUB> 
  emissions, the emissions matrix and integrate them into the CVRP Model and proposes 
  a genetic algorithm to solve this problem. The effectiveness of this approach 
  is tested on a well-known set of benchmarks and compared to other works from 
  literature.
ER  -