基于模糊群决策的绿色供应商选择和订单分配方法

doi:10.16182/j.issn1004731x.joss.23-FZ0808E

摘要/Abstract

摘要：

随着市场竞争愈发激烈、全球环境日益恶化以及公众环保意识的提高，绿色采购问题受到了广泛关注。现有研究绝大多数聚焦于考虑绿色准则的供应商选择问题，以实现可持续经营。然而，在综合考虑时间、价格和成本等因素的前提下，从适应性强的供应商处获得适当的产品，对于企业来说更为可行和经济，即供应商选择和订单分配。为了解决上述关键问题，提出了一种模糊环境下的多准则群体决策方法。提出了一种基于理想解相似性偏好排序和层次分析法（technique for order of preference by similarity to ideal solution and analytic hierarchy process，TOPSIS-AHP）的模糊排序方法，该方法可根据企业战略灵活调整传统准则和绿色准则的权重。在双目标优化模型中引入供应商排名进行订货，在实现采购绩效最大化的同时，最大限度地降低采购成本。结果表明：所提方法能够有效评价供应商绩效，并优化候选供应商之间的订单分配。

关键词: 供应商选择, 订单分配, 模糊群决策, technique for order of preference by similarity to ideal solution and analytic hierarchy process(TOPSIS-AHP), 双目标优化

Abstract:

With the intensity of market competitiveness, the worsening of the global environment, and the improvement of public concern about environmental protection, the issue of green purchasing has received considerable attention. The vast majority of existing studies on green purchasing have concentrated on supplier selection with green criteria, so as to realize sustainable operations, whereas it is more feasible and economical for businesses to obtain the proper products from adaptable and suitable suppliers at the right times, rates, and volumes, which is referred to as supplier selection and order allocation. To resolve the aforementioned two crucial challenges, we propose a group decision-making method within an ambiguous context. A fuzzy ranking approach based on the technique for order of preference by similarity to ideal solution and analytic hierarchy process (TOPSIS-AHP) is addressed. The proposed solution enables each of the green and classical criteria to be given a flexible preference under the organization's strategy. Supplier ranks are utilized in a bi-objective optimization model to allocate orders, where the procurement performance is maximized while the entire procurement cost is minimized. The findings show that the proposed method is capable of assessing the performance of providers and optimizing the distribution of orders among candidate suppliers.

Key words: supplier selection, order allocation, fuzzy group decision-making, technique for order of preference by similarity to ideal solution and analytic hierarchy process(TOPSIS-AHP), bi-objective optimization

中图分类号:

TP391.9

刘路,李文欣,宋晓等 . 基于模糊群决策的绿色供应商选择和订单分配方法[J]. 系统仿真学报, 2023, 35(10): 2133-2149.

Liu Lu,Li Wenxin,Song Xiao,et al . A Fuzzy Group Decision-making-based Method for Green Supplier Selection and Order Allocation[J]. Journal of System Simulation, 2023, 35(10): 2133-2149.

图/表 29

	Case A	Case B	Case C	Case D
Aggregated fuzzy rating	$x i j = 1 N ∑ n = 1 N x i j n y i j = 1 N ∑ n = 1 N y i j n z i j = 1 N ∑ n = 1 N z i j n$	$x i j = 1 N ∑ n = 1 N x i j n y i j = 1 N ∑ n = 1 N y i j n z i j = 1 N ∑ n = 1 N z i j n$	$x i j = m i n n x i j n y i j = 1 N ∑ n = 1 N y i j n z i j = m a x n z i j n$	$x i j = m i n n x i j n y i j = 1 N ∑ n = 1 N y i j n z i j = m a x n z i j n$
Aggregated fuzzy weight	$α j 1 = 1 N ∑ n = 1 n α j 1 n α j 2 = 1 N ∑ n = 1 n α j 2 n α j 3 = 1 N ∑ n = 1 n α j 3 n$	$α j 1 = 1 N ∑ n = 1 n α j 1 n α j 2 = 1 N ∑ n = 1 n α j 2 n α j 3 = 1 N ∑ n = 1 n α j 3 n$	$α j 1 = m i n n α j 1 n α j 2 = 1 N ∑ n = 1 N α j 2 n α j 3 = m a x n α j 3 n$	$α j 1 = m i n n α j 1 n α j 2 = 1 N ∑ n = 1 N α j 2 n α j 3 = m a x n α j 3 n$
FPIS	$u ˜ j + = (1,1, 1)$	$u ˜ j + = m a x i (u i j 1, u i j 2, u i j 3)$	$u ˜ j + = (1,1, 1)$	$u ˜ j + = m a x i (u i j 1, u i j 2, u i j 3)$
FNIS	$u ˜ j - = (0,0, 0)$	$u ˜ j - = m i n i (u i j 1, u i j 2, u i j 3)$	$u ˜ j - = (0,0, 0)$	$u ˜ j - = m i n i (u i j 1, u i j 2, u i j 3)$

$ω 1 / ω 2$	$β G / β T$
$ω 1 / ω 2$	0.2/0.8	0.4/0.6	0.6/0.4	0.8/0.2
0.1/0.9	4 280.660	4 350.212	4 419.763	4 489.315
0.3/0.7	4 322.240	4 383.435	4 444.630	4 505.825
0.5/0.5	4 387.232	4 411.947	4 474.198	4 536.449
0.7/0.3	4 416.676	4 440.459	4 498.614	4 541.553
0.9/0.1	4 416.676	4 464.100	4 511.525	4 558.949

$ω 1 / ω 2$	$β G / β T$
$ω 1 / ω 2$	0.2/0.8	0.4/0.6	0.6/0.4	0.8/0.2
0.1/0.9	4 751.198	4 524.612	4 298.025	4 056.929
0.3/0.7	4 964.222	4 713.060	4 398.345	4 186.639
0.5/0.5	5 070.365	4 795.543	4 478.617	4 205.839
0.7/0.3	5 070.365	4 795.543	4 520.720	4 229.935
0.9/0.1	5 070.365	4 795.543	4 520.720	4 245.898

$ω 1 / ω 2$	$β G / β T$
$ω 1 / ω 2$	0.2/0.8	0.4/0.6	0.6/0.4	0.8/0.2
0.1/0.9	4 703.152	4 474.735	4 246.319	4 020.128
0.3/0.7	4 906.480	4 664.431	4 363.439	4 147.502
0.5/0.5	4 995.489	4 738.221	4 441.903	4 201.934
0.7/0.3	4 995.489	4 738.221	4 480.953	4 223.685
0.9/0.1	4 995.489	4 738.221	4 480.953	4 223.685

$ω 1 / ω 2$	$β G / β T$
$ω 1 / ω 2$	0.2/0.8	0.4/0.6	0.6/0.4	0.8/0.2
0.1/0.9	4 074.115	4 149.426	4 224.738	4 300.049
0.3/0.7	4 107.040	4 176.199	4 241.639	4 311.608
0.5/0.5	4 158.304	4 176.199	4 245.359	4 335.254
0.7/0.3	4 184.698	4 219.687	4 281.071	4 335.254
0.9/0.1	4 184.698	4 240.025	4 295.353	4 345.910

Supplier	$β G / β T$
Supplier	0.2/0.8	0.4/0.6	0.6/0.4	0.8/0.2
Sum	2.354 4	2.423 8	2.493 2	2.562 6
1	0.561 6	0.580 2	0.598 8	0.617 4
2	0.690 6	0.683 2	0.675 8	0.668 4
3	0.618 8	0.639 6	0.660 4	0.681 2
4	0.483 4	0.520 8	0.558 2	0.595 6

Supplier	$β G / β T$
Supplier	0.2/0.8	0.4/0.6	0.6/0.4	0.8/0.2
Sum	2.302 8	2.257 6	2.212 4	2.167 2
1	0.518 8	0.488 6	0.458 4	0.428 2
2	0.896 2	0.828 4	0.760 6	0.692 8
3	0.665 8	0.666 6	0.667 4	0.668 2
4	0.222 0	0.274 0	0.326 0	0.378 0

$ω 1 / ω 2$	Case A		Case B		Case C		Case D
$ω 1 / ω 2$	TCP	TVP	TCP	TVP	TCP	TVP	TCP	TVP
0.1/0.9	205 230.8	4 280.660	205 529.2	4 703.152	205 230.8	4 074.115	205 529.2	4 751.198
0.2/0.8	205 449.2	4 315.470	206 462.2	4 795.312	205 449.2	4 101.700	205 529.2	4 751.198
0.3/0.7	205 529.2	4 322.240	208 012.2	4 906.480	205 529.2	4 107.040	208 012.2	4 964.222
0.4/0.6	205 529.2	4 322.240	208 012.2	4 906.480	205 529.2	4 107.040	210 665.4	5 070.365
0.5/0.5	208 012.2	4 387.232	210 665.4	4 995.489	208 012.2	4 158.304	210 665.4	5 070.365
0.6/0.4	208 012.2	4 387.232	210 665.4	4 995.489	208 012.2	4 158.304	210 665.4	5 070.365
0.7/0.3	210 665.4	4 416.676	210 665.4	4 995.489	210 665.4	4 184.698	210 665.4	5 070.365
0.8/0.2	210 665.4	4 416.676	210 665.4	4 995.489	210 665.4	4 184.698	210 665.4	5 070.365
0.9/0.1	210 665.4	4 416.676	210 665.4	4 995.489	210 665.4	4 184.698	210 665.4	5 070.365

$ω 1 / ω 2$	Case A		Case B		Case C		Case D
$ω 1 / ω 2$	TCP	TVP	TCP	TVP	TCP	TVP	TCP	TVP
0.1/0.9	205 230.8	4 489.315	205 538.2	4 020.128	205 230.8	4 300.049	205 449.2	4 056.929
0.2/0.8	205 230.8	4 489.315	206 462.2	4 147.502	205 230.8	4 300.049	206 462.2	4 186.639
0.3/0.7	205 529.2	4 505.825	206 462.2	4 147.502	205 449.2	4 311.608	206 462.2	4 186.639
0.4/0.6	205 538.2	4 506.209	206 982.2	4 169.102	205 529.2	4 314.518	206 982.2	4 205.839
0.5/0.5	206 462.2	4 536.449	208 532.2	4 201.934	206 462.2	4 335.254	206 982.2	4 205.839
0.6/0.4	206 462.2	4 536.449	208 532.2	4 201.934	206 462.2	4 335.254	208 532.2	4 229.935
0.7/0.3	206 982.2	4 541.553	210 665.4	4 223.685	206 462.2	4 335.254	208 532.2	4 229.935
0.8/0.2	208 532.2	4 552.017	210 665.4	4 223.685	206 982.2	4 338.710	210 665.4	4 245.898
0.9/0.1	210 665.4	4 558.949	210 665.4	4 223.685	208 532.2	4 345.910	210 665.4	4 245.898

$ω 1 / ω 2$	Case A		Case B		Case C		Case D
$ω 1 / ω 2$	TCP	TVP	TCP	TVP	TCP	TVP	TCP	TVP
0.1/0.9	205 230.8	4 350.212	205 529.2	4 474.735	205 230.8	4 149.426	205 529.2	4 524.612
0.2/0.8	205 449.2	4 377.495	206 462.2	4 579.375	205 449.2	4 171.669	205 529.2	4 524.612
0.3/0.7	205 529.2	4 383.435	208 012.2	4 664.431	205 529.2	4 176.199	208 012.2	4 713.060
0.4/0.6	205 529.2	4 383.435	208 012.2	4 664.431	205 529.2	4 176.199	208 012.2	4 713.060
0.5/0.5	206 462.2	4 411.947	210 665.4	4 738.221	205 529.2	4 176.199	210 665.4	4 795.543
0.6/0.4	208 012.2	4 440.459	210 665.4	4 738.221	208 012.2	4 219.687	210 665.4	4 795.543
0.7/0.3	208 012.2	4 440.459	210 665.4	4 738.221	208 012.2	4 219.687	210 665.4	4 795.543
0.8/0.2	210 665.4	4 464.100	210 665.4	4 738.221	210 665.4	4 240.025	210 665.4	4 795.543
0.9/0.1	210 665.4	4 464.100	210 665.4	4 738.221	210 665.4	4 240.025	210 665.4	4 795.543

$ω 1 / ω 2$	Case A		Case B		Case C		Case D
$ω 1 / ω 2$	TCP	TVP	TCP	TVP	TCP	TVP	TCP	TVP
0.1/0.9	205 230.8	4 419.763	205 529.2	4 246.319	205 230.8	4 224.738	205 529.2	4 298.025
0.2/0.8	205 449.2	4 439.520	206 462.2	4 363.439	205 230.8	4 224.738	206 462.2	4 398.345
0.3/0.7	205 529.2	4 444.630	206 462.2	4 363.439	205 449.2	4 241.639	206 462.2	4 398.345
0.4/0.6	205 529.2	4 444.630	208 532.2	4 441.903	205 529.2	4 245.359	208 012.2	4 461.897
0.5/0.5	206 462.2	4 474.198	208 532.2	4 441.903	205 529.2	4 245.359	208 532.2	4 478.617
0.6/0.4	206 462.2	4 474.198	210 665.4	4 480.953	206 462.2	4 264.271	210 665.4	4 520.720
0.7/0.3	208 532.2	4 498.614	210 665.4	4 480.953	208 012.2	4 281.071	210 665.4	4 520.720
0.8/0.2	210 665.4	4 511.525	210 665.4	4 480.953	208 532.2	4 284.223	210 665.4	4 520.720
0.9/0.1	210 665.4	4 511.525	210 665.4	4 480.953	210 665.4	4 295.353	210 665.4	4 520.720

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Linguistic variable	TFN
Very low (VL)	(0, 0, 0.1)
Low (L)	(0, 0.1, 0.3)
Medium low (ML)	(0.1, 0.3, 0.5)
Medium (M)	(0.3, 0.5, 0.7)
Medium high (MH)	(0.5, 0.7, 0.9)
High (H)	(0.7, 0.9, 1.0)
Very high (VH)	(0.9, 1.0, 1.0)

Linguistic variable	TFN
Very poor (VP)	(0, 0, 1)
Poor (P)	(0, 1, 3)
Medium poor (MP)	(1, 3, 5)
Fair (F)	(3, 5, 7)
Medium good (MG)	(5, 7, 9)
Good (G)	(7, 9, 10)
Very good (VG)	(9, 10, 10)

Intensity of importance	Definition
1	Equally important
3	Moderately important
5	Very important
7	Strongly important
9	Extremely important
2, 4, 6, 8	Intermediate values

Supplier	1st phase	2nd phase	3rd phase	4th phase
1	2 792	2 923	2 718	2 953
2	2 602	2 589	2 655	2 990
3	2 645	2 615	2 962	2 719
4	2 730	2 585	2 715	2 555

Phase	Demand	Holding cost	Shortage cost	Available Suppliers
1	1 750	4	8	S1, S2, S3, S4
2	1 800	4	9	S1, S2, S3
3	1 765	3	8	S2, S3
4	1 630	5	8	S1, S2, S4