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A simulated annealing heuristic for the capacitated green vehicle routing problem
Normasari N.M.E.a,b, Yu V.F.a, Bachtiyar C.a, Sukoyoc
a Department of Industrial Management, National Taiwan University of Science and Technology, Taipei, 10607, Taiwan
b Department of Mechanical and Industrial Engineering, Gadjah Mada University, Yogyakarta, 55281, Indonesia
c Department of Industrial Engineering and Management, Institut Teknologi Bandung, Bandung, Jawa Barat, Indonesia
[vc_row][vc_column][vc_row_inner][vc_column_inner][vc_separator css=”.vc_custom_1624529070653{padding-top: 30px !important;padding-bottom: 30px !important;}”][/vc_column_inner][/vc_row_inner][vc_row_inner layout=”boxed”][vc_column_inner width=”3/4″ css=”.vc_custom_1624695412187{border-right-width: 1px !important;border-right-color: #dddddd !important;border-right-style: solid !important;border-radius: 1px !important;}”][vc_empty_space][megatron_heading title=”Abstract” size=”size-sm” text_align=”text-left”][vc_column_text]© 2019 Nur Mayke Eka Normasari et al.This research studies the capacitated green vehicle routing problem (CGVRP), which is an extension of the green vehicle routing problem (GVRP), characterized by the purpose of harmonizing environmental and economic costs by implementing effective routes to meet any environmental concerns while fulfilling customer demand. We formulate the mathematical model of the CGVRP and propose a simulated annealing (SA) heuristic for its solution in which the CGVRP is set up as a mixed integer linear program (MILP). The objective of the CGVRP is to minimize the total distance traveled by an alternative fuel vehicle (AFV). This research conducts a numerical experiment and sensitivity analysis. The results of the numerical experiment show that the SA algorithm is capable of obtaining good CGVRP solutions within a reasonable amount of time, and the sensitivity analysis demonstrates that the total distance is dependent on the number of customers and the vehicle driving range.[/vc_column_text][vc_empty_space][vc_separator css=”.vc_custom_1624528584150{padding-top: 25px !important;padding-bottom: 25px !important;}”][vc_empty_space][megatron_heading title=”Author keywords” size=”size-sm” text_align=”text-left”][vc_column_text]Alternative fuel vehicles,Customer demands,Environmental concerns,Mixed integer linear program,Numerical experiments,Research studies,Total distances,Vehicle Routing Problems[/vc_column_text][vc_empty_space][vc_separator css=”.vc_custom_1624528584150{padding-top: 25px !important;padding-bottom: 25px !important;}”][vc_empty_space][megatron_heading title=”Indexed keywords” size=”size-sm” text_align=”text-left”][vc_column_text][/vc_column_text][vc_empty_space][vc_separator css=”.vc_custom_1624528584150{padding-top: 25px !important;padding-bottom: 25px !important;}”][vc_empty_space][megatron_heading title=”Funding details” size=”size-sm” text_align=”text-left”][vc_column_text]This research was funded by Badan Penerbit dan Publikasi (BPP) of Gadjah Mada University and the Ministry of Science and Technology of the Republic of China (Taiwan) under grant MOST 106-2410-H-011-002-MY3. This research is based on Mr. Candra Bachtiyar’s thesis.[/vc_column_text][vc_empty_space][vc_separator css=”.vc_custom_1624528584150{padding-top: 25px !important;padding-bottom: 25px !important;}”][vc_empty_space][megatron_heading title=”DOI” size=”size-sm” text_align=”text-left”][vc_column_text]https://doi.org/10.1155/2019/2358258[/vc_column_text][/vc_column_inner][vc_column_inner width=”1/4″][vc_column_text]Widget Plumx[/vc_column_text][/vc_column_inner][/vc_row_inner][/vc_column][/vc_row][vc_row][vc_column][vc_separator css=”.vc_custom_1624528584150{padding-top: 25px !important;padding-bottom: 25px !important;}”][/vc_column][/vc_row]