考虑能量消耗的纯电动物流车柔性时间窗路径规划问题

doi:10.13229/j.cnki.jdxbgxb.20210822

Abstract

Abstract:

Vehicle Routing Problem （VRP） with flexible time window is useful to increase the profits of logistics companies by loosening the time constraints with less penalty cost. In this paper， the electric logistics vehicle routing problem with flexible time window （EVRP-FlexTW） is studied as a model driven experimental approach. Firstly， an energy consumption model considering the start-brake process is proposed for electric logistics vehicles to reveal their characteristics of energy consumption. Then the influence of energy consumption is integrated into the EVRP-FlexTW model with minimum total distribution cost in consideration in additional constraints such as vehicle loading capacity， flexible time window and electrical energy. The improved Ant Colony Algorithm is also designed to solve the model. Sensitivity analysis on the trip speed and flexible time window impact to the proposed model shows that reducing the maximum driving speed is generally contributed to get the better routing solution. Satisfying the constraints of flexible time window cannot shorten the distribution distance or reduce the electricity consumption of electric vehicles but can achieve the lowest total distribution cost. As a whole， those founding can come to the proposed model validation.

Key words: transportation planning, flexible time window, electric delivery vehicles, vehicle routing problem, energy consumption estimation model

CLC Number:

N945.15

Bao-feng SUN,Jiao-jiao LIU,Tian-zi YAO,Xin-xin REN. Electric delivery vehicle routing problem with flexible time window integrated with energy consumption estimation[J].Journal of Jilin University(Engineering and Technology Edition), 2023, 53(4): 1047-1059.

Figures/Tables 7

Fig.1

Table 1

The lowest total cost distribution scheme"

车辆编号	行驶路径顺序 $r o u t e$	总载重 $S u m l o a d$ /kg	总耗电量 $E$ /（kW·h）	总距离 $D$ /km	总时间 $t$ /min
合计		3696.16	248.57	623.59	1090.54
1	0→7→1→11→2→3→4→6→D→8→10→0	1289.28	88.05	221.36	411.16
2	0→13→5→9→16→15→I→14→20→24→17→0	1363.20	103.65	258.18	449.32
3	0→18→12→25→19→21→23→22→0	1043.68	56.87	144.05	230.06

Table 1

Table 2

eˉij of electric logistics vehicles at different vˉij"

$v ˉ i j$		$d ˉ i j$ =50 m	$d ˉ i j$ =200 m	$d ˉ i j$ =350 m	$d ˉ i j$ =500 m	$d ˉ i j$ =650 m	$d ˉ i j$ =800 m	$d ˉ i j$ =900 m	$d ˉ i j$ =990 m
变速	48 km/h	0.074	0.188	0.228	0.267	0.306	0.346	0.372	0.309
	54 km/h	0.075	0.228	0.272	0.315	0.359	0.403	0.407	0.342
	60 km/h	0.076	0.292	0.340	0.389	0.442	0.510	0.492	0.428
匀速	48 km/h	0.013	0.053	0.092	0.131	0.171	0.210	0.236	0.260
	54 km/h	0.015	0.058	0.102	0.146	0.190	0.233	0.262	0.289
	60 km/h	0.016	0.065	0.113	0.162	0.210	0.259	0.291	0.320

Table 2

Fig.2

Fig.3

Table 3

Comparison of solution results under different vˉij"

$v ˉ i j$ /（km·h^-1）	$n *$ /辆	$D$ /km	$W$	$E$ /（kW·h）	$T C$ /元
60	3	648.47	0.782	298.37	832.42
54	3	623.59	0.789	248.56	783.65
48	3	542.8	0.791	184.99	618.48
42	3	576.92	0.792	168.97	493.29
36	3	593.26	0.790	147.63	443.33
30	4	639.48	0.497	148.44	619.87

Table 3

Table 4

Solution results comparison of combination of flexible time window coefficients"

客户数量N	时间窗系数组合	$n *$ /辆	$D$ /km	$W$	$E$ /（kW·h）	$T C$ /元
$15$	（1） $p i = 0.25, (C e, C d) = (0.5,1.0)$	2	422.42	0.703	166.47	536.86
	（2） $p i = 0.50, (C e, C d) = (0.5,1.0)$	2	407.33	0.706	160.90	502.02
	（3） $p i = 0.25, (C e, C d) = (2.0,4.0)$	2	429.27	0.697	168.82	599.21
	（4） $p i = 0.50, (C e, C d) = (2.0,4.0)$	2	425.21	0.705	167.15	562.89
	（5） $无 p i, (C e, C d) = (0.5,1.0)$	2	364.10	0.702	143.42	603.82
	（6） $无 p i, (C e, C d) = (2.0,4.0)$	2	430.64	0.706	169.43	851.50
$25$	（7） $p i = 0.25, (C e, C d) = (0.5,1.0)$	3	623.59	0.789	248.56	783.64
	（8） $p i = 0.50, (C e, C d) = (0.5,1.0)$	3	579.06	0.790	230.75	762.18
	（9） $p i = 0.25, (C e, C d) = (2.0,4.0)$	3	628.04	0.778	259.11	1255.07
	（10） $p i = 0.50, (C e, C d) = (2.0,4.0)$	3	604.93	0.790	240.7675	1052.62
	（11） $无 p i, (C e, C d) = (0.5,1.0)$	3	606.35	0.788	241.63	983.73
	（12） $无 p i, (C e, C d) = (2.0,4.0)$	3	688.39	0.789	274.5864	1418.52

Table 4

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