Academic Journal of Science and Technology 
ISSN: 2771-3032 | Vol. 11, No. 3, 2024 

 

226 

Research	on	Supermarket	Layout	Optimization	based	
on	SLP	and	AHP‐FCE	
Shichang Ren 

Department of IEM, Southwest Petroleum University, Chengdu, China 

 

Abstract: The layout of a supermarket directly impacts customers' shopping experiences and operational efficiency. A well-
designed layout facilitates smooth shopping experiences for customers while enhancing the operational efficiency and 
profitability of the supermarket. With the impact of e-commerce on traditional retail, redesigning supermarket layouts holds 
significant importance. This paper takes the layout planning of M Supermarket as a case study. It begins with on-site inspections 
and the creation of a floor plan. Subsequently, random surveys are conducted with customers who have completed their shopping. 
Instead of traditional SLP using the flow of goods, customer foot traffic is considered to refine non-logistical factors, resulting 
in relative position maps and feasible supermarket layout proposals. Finally, the effectiveness of both old and new layout schemes 
is evaluated using the AHP-fuzzy comprehensive evaluation method. 

Keywords: Layout Optimization; SLP; AHP-Fuzzy Comprehensive Evaluation. 
 

1. Introduction 
With changes in people's living standards and consumption 

patterns (as shown in Table 1), traditional brick-and-mortar 
businesses struggle to meet the increasing material 
consumption demands of the populace. Since the 1990s, with 
the introduction of chain operations, China's chain 
supermarkets have experienced rapid development as an 
emerging retail industry. As competition among supermarkets 
intensifies in the 21st century, there is a growing necessity to 
improve supermarket competitiveness through rational layout 
planning. Careful design and the application of scientific 
knowledge in layout optimization can create a better shopping 
environment within these new commercial entities. 

 
Table 1. Changes in types of consumption 

Decade The 1908s The 1990s Modernity 

Type of 
consumption 

Survivability 
Survival 

and 
enjoyment 

Experiential 
and service-

oriented
Source: Beijing Statistical Information Network 

2. SLP Methodology 
Systematic Layout Planning (SLP) was proposed by 

American expert Richard Muther in 1961 [1]. This method is 
a systematic and logical approach that combines logistics 
analysis with the analysis of relationships between 
operational units to achieve an optimal layout. SLP utilizes 
concepts heavily quantified with mathematical relationships 
to establish logistics correlations between various operational 
units and non-logistical relationships. This forms a 
mathematical model for facility planning and layout. The 
combination of chart analysis, graphical models, qualitative, 
and quantitative analysis ensures the scientific rationality of 
the entire system's facility planning. 

Initially, the primary focus of SLP was on the layout design 
of factories and production facilities [2,3], aiming to enhance 
production efficiency and working environments. As 
understanding and practical experience in applying SLP 
method accumulated, its application scope gradually 
expanded beyond factories and production facilities. It now 

encompasses various types of facilities such as offices, 
medical facilities, commercial establishments, and others, 
reflecting its adaptability and effectiveness across diverse 
settings. 

In 2005, Qi Xiumei shifted the focus from the perspective 
of operators to consumers and improved the traditional SLP 
method by replacing its original five basic elements with 
seven. This revised method was then applied to the planning 
and design of supermarket layouts [4]. Sun Junhua et al. (2006) 
conducted research on two large supermarkets in Shanghai, 
clarifying the fundamental elements and confirming that the 
SLP method could indeed be applied to the overall layout 
design of large supermarkets [5]. 

As the traditional SLP method becomes widely used in 
layout planning, its inherent limitations have gradually 
become apparent. For instance, it often fails to adequately 
consider various complex non-logistical factors and lacks 
validation and feedback mechanisms for selected layout 
schemes. Addressing these issues, Huang Zezhen et al. (2013) 
proposed considering customer foot traffic as the primary 
factor in determining the logistics relationships between 
various operational units [6]. Furthermore, Liu Zhihai et al. 
(2017) suggested conducting a more detailed analysis of non-
logistical factors among operational units influencing 
supermarket layouts to ensure comprehensive layout schemes. 
They also recommended performing circulation analysis on 
selected schemes and incorporating the results as feedback to 
optimize the final layout plan [7]. 

Customer foot traffic has thus become a crucial 
consideration in the application of the improved SLP method 
for supermarket layouts. Wang Xueqin et al. (2016) made 
improvements to the traditional SLP method, focusing on 
logistics analysis to further explore relationships between 
functional areas. This enhancement aimed to improve the 
overall integration between functional areas and optimize the 
overall layout scheme [8]. 

Zhao Feng et al. (2018) conducted layout optimization 
using the movement line-based SLP method at a specific 
supermarket. They initially analyzed the interrelations 
between various merchandise sections. After obtaining 
relative position maps and new layout schemes, they utilized 



 

227 

the Analytic Hierarchy Process (AHP) for comparative 
evaluation of the new layout schemes [9]. 

This article takes the layout planning of M Supermarket as 
an example. Firstly, on-site inspections are conducted, and 
layout diagrams are drawn. Then, feasible layout schemes are 
proposed by replacing goods flow with customer foot traffic 
and refining non-logistical factors. Subsequently, the AHP-
fuzzy comprehensive evaluation method is employed to 
assess the schemes. 

3. Application of Improved SLP in 
Supermarket Layout 

3.1. Introduction to M Supermarket 
M Supermarket opened in 2006, specializing in vegetables, 

fruits, and household items. Operating hours are from 9:00 to 
21:30. Through on-site investigation and layout mapping, it 
was determined that the supermarket is divided into 24 areas, 
covering daily commodities and household essentials, with 
alternating arrangements of these areas. The vegetable section 
is divided into two parts, located in the northwest corner along 
with the fruit, fresh meat and seafood, and grains and oils 
sections. Household items, kitchenware, books, paper 
products, bulk food, imported goods, and toys are arranged on 
both sides of the entrance to attract customers' attention. The 
areas for personal care products and stationery are arranged 
longitudinally, dividing the supermarket into two sections. 
The right half of the supermarket houses condiments, 
alcoholic and beverages, and snacks, with shelves arranged 
horizontally, resulting in narrow and densely packed aisles. 
The frozen goods and dairy products sections are located at 
the far right of the supermarket. The layout of the supermarket 
is illustrated in Figure 1. 

 
fruits fresh meat and seafood cooked food bakery

vegetables
household 

item
s

kitchenw
are

B
ooks

vegetables

bulk food

Promotional
 items

grains 
and oils

imported 
food

paper 
products

entrance

personal care products
stationery

toys

condiments

 alcoholic and 
beverages

snacks

candy and 
chocolate

Promotional
 items

Promotional
 items

 dairy 
products

snacks

snacks

dried fruit

frozen food
 dairy products

rice and 
flour

frozen 
food

 dairy 
products

Instant 
food 

Checkout counter

 
Fig 1. M Supermarket layout 

 
From the observation of the layout diagram, it can be seen 

that in terms of logistics, the aisle width of the supermarket is 
also different due to the placement of shelves, which is easy 
to cause blockage in the area with dense customers, and the 
process of replenishment and withdrawal becomes 
cumbersome. For example, there is a potential risk of 
blockage in the corner formed by the three areas of fruit, fresh 
meat and seafood and vegetables. In terms of the size of each 
area, the difference in the number and size of shelves leads to 
the difference in the area of each area. The area of goods that 
customers most often buy is often larger, and the area of non-
necessities such as candy and chocolate, snacks area is small 
and concentrated. Through the inquiry of the supermarket 
staff, we learned that the promotional items and paper 
products area are special containers because their products 
can be stored for a long time. There is storage space at the 
bottom, which can store some goods to be put on the shelves, 
and replenishment is easier. In order to ensure the freshness 
of the food, the fruit area and vegetable area need to pick up 
the goods from the warehouse behind the bakery area and the 
frozen food area every time, which is easy to lead to the 
replenishment of the goods is not timely and the route is far. 

3.2. Analysis of Basic Elements 
For a specialized service industry like supermarkets, it's 

crucial to identify the basic elements of raw data. The five 
fundamental elements are as follows: P - People, Q - 
Customer Traffic, R - Customer Shopping Routes, S - 
Checkout Counter Areas, T - Customer Shopping Time. 
Through a scientifically rational analysis of these elements, 
the interrelations between different areas can be determined 
[5]. 

3.3. Logistics Relationship Analysis 
According to the improved SLP method [10], the logistics 

relationships and non-logistics relationships of each 
operational unit need to be determined sequentially. Finally, 
the comprehensive proximity of each operational unit is 
calculated by combining weights. Due to the different service 
nature of supermarkets compared to warehouses, this paper 
will use customer foot traffic of each operational unit instead 
of traditional SLP methods' flow of goods [6]. Surveys and 
statistics will be conducted to gather customer foot traffic data 
for each operational unit in the supermarket, obtaining the 
proportion of customer foot traffic for each unit, as shown in 
Table 2. 

 
Table 2. The proportion of customer foot traffic 

Area proportion Area proportion Area proportion 

A: vegetables 66.67% I: dairy products 22.96% Q: candy and chocolate 14.07%
B: fruits 46.67% J: cooked food 21.48% R: alcoholic and beverages 12.59%

C: grains and oils 33.33% 
K: personal care 

products
20.74% S: instant food 9.63% 

D: condiments 32.59% L: bakery 19.26% T: toys 6.67% 

E: fresh meat and seafood 28.15% M: dried fruit 17.78% U: kitchenware 5.93% 

F: rice and flour 27.41% N: bulk food 17.04% V: imported food 4.44% 

G: paper    products 26.67% O: household items 16.29% W: stationery 3.70% 

H: frozen   food 25.19% P: snacks 14.81% X: books 1.48% 

After obtaining the customer foot traffic data, the next step 
is to determine the closeness between each area. This is done 

by categorizing the levels of closeness based on the 
differences in customer foot traffic between the units. 



 

228 

Specifically, the difference in customer foot traffic is 
calculated, and the closeness is determined according to the 
magnitude of these differences [6]. The formula for 
calculating the difference in customer foot traffic is shown in 
Formula 1 below: 

              Z=|Pi-Pi+1|                   (1) 
 

In the formula, Pi represents the customer foot traffic of the 
i-th area. 

According to the relevant reference [6], the calculated 
differences in customer foot traffic should be assigned values 
based on the following ranges: 0%–6%, 6%–12%, 12%–18%, 
18%–24%, 24%–30%, and above 30%. These ranges are 
categorized into five levels: A, E, I, O, U, X, with importance 
values assigned as follows: 5, 4, 3, 2, 1, 0, respectively. Based 
on the above, the logistics relationships between each area can 
be determined, as shown in Figure 2. 

 
Fig 2. Logistics relationship 

3.4. Non-Logistics Relationship Analysis 
In supermarket layout planning, besides considering 

customer foot traffic as the primary logistics factor, non-
logistics factors must also be taken into account. Based on 
inquiries with M Supermarket staff and relevant literature [6], 
the main non-logistics factors influencing inter-area 
relationships include the convenience of restocking, ease of 
staff communication, proximity to the exit, comfort of the 
shopping environment, continuity of space usage, 
complementarity of products, and the rationality of guided 
shopping routes. These factors are sequentially coded as 1, 2, 
3, 4, 5, 6, and 7. 

The non-logistics relationship levels between each area are 
categorized into six levels: A (Absolutely Related), E (Highly 
Related), I (Moderately Related), O (Generally Related), U 
(Lowly Related), and X (Not Related), with values assigned 
from high to low as 5, 4, 3, 2, 1, and 0, respectively [6] The 
non-logistics relationships are judged and graded based on the 
distance factors between each area. The non-logistics 
relationships are illustrated in Figure 3. 

 
Fig 3. Non-Logistics relationship 

3.5. Comprehensive Relationship Analysis 
The comprehensive relationships between each area 

include logistics relationships (X) and non-logistics 
relationships (Y). Since customer foot traffic is a primary 
factor for supermarkets, logistics relationships should have a 
higher weight compared to non-logistics relationships, with a 
weight ratio of X:Y = 3:2. By using this ratio and the formula, 
the comprehensive mutual relationship scores and overall 
relationships between areas can be determined. 

Zij= ×Xij+ ×Yij                         (2) 

In the formula: 
Zij- Comprehensive relationship score between operational 

units i and j; 
Xij- Logistics relationship score between operational units i 

and j; 
Yij - Non-logistics relationship score between operational 

units i and j. 
In summary, the comprehensive mutual relationships are 

shown in Figure 4. 
vegetables

fruits

grains 
and oils

condiments

fresh meat 
and seafood

rice and flour

 paper 
products

 frozen food

dairy 
products 

cooked food

personal care 
 products

bakery 

dried fruit

bulk food

household 
items

snacks

candy and 
chocolate

alcoholic and 
beverages

 instant food

toys

kitchenware

imported 
food

stationery

books

I
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Fig 4. Comprehensive Mutual Relationships 



 

229 

3.6. Layout Based on Comprehensive Mutual 
Relationships 

The values and rankings of the comprehensive proximity 

of each area are shown in Table 3. 

 
Table 3. Comprehensive Proximity Ranking Table for Each Area 

Area 
Code 

Area 
Comprehensive 

Proximity 
Ranking 

Area 
Code 

Area 
Comprehensive 

Proximity 
Ranking 

A vegetables 16 24 M dried fruit 61 1 

B fruits 23 22 N bulk food 57 3 

C grains and oils 44 12 O household items 33 16 

D condiments 40 15 P snacks 56 4 

E 
fresh meat 

and seafood 
49 11 Q 

candy and 
chocolate 

53 7 

F rice and flour 53 7 R 
alcoholic and 

beverages
50 10 

G paper products 28 18 S instant food 43 13 

H frozen food 56 4 T toys 26 19 

I dairy products 52 9 U kitchenware 25 21 

J cooked food 60 2 V imported food 41 14 

K personal care 
products 

29 17 W stationery 26 19 

L bakery 55 6 X books 22 23 

Based on the comprehensive mutual relationships and 
comprehensive proximity of each area, areas with higher 
proximity scores should be placed in central locations, while 
those with lower scores should be positioned at the periphery. 
According to the rankings, the "Dried Fruits Section" should 
be placed in the central position. Then, the positions of other 
areas are determined based on their comprehensive mutual 
relationship scores with the central area. For areas within the 
same level, those with higher overall scores should be 
prioritized. 

Based on the positional correlation chart of each area, the 
comprehensive proximity, and the area of each area in the 
supermarket, adjustments were made to the original layout to 
derive the improved layout, as shown in Figure 5. 

In terms of overall layout, the dried fruit section, with the 
highest comprehensive proximity, is placed in the central area 
of the supermarket, with other high-scoring areas surrounding 
it. Regarding aisles, compared to the old layout, the new 
spatial arrangement eliminates the vertical shelves in the 
middle of the supermarket, widening the aisles to facilitate the 
flow of both logistics and foot traffic. Additionally, some 
low-utilization checkout counters are removed, and three self-
checkout lanes are added along with a no-shopping lane, 
increasing the checkout speed and dispersing foot traffic. 

Regarding area settings, the new layout eliminates vertical 
shelving, resulting in all areas of the supermarket, except for 
the edge regions, having horizontal orientations. This reduces 
unnecessary turning routes for customers. Some areas are 
reduced in size, while the area for fresh meat and seafood is 
expanded. Furthermore, the fresh meat and seafood section is 
separated from the vegetable, fruit, bakery, and cooked food 
sections to prevent the odor from affecting other edible goods, 
thus enhancing customer satisfaction. In terms of 
replenishment convenience, the width of replenishment ports 
is increased, improving the overall flow of the supermarket's 
aisles and facilitating logistical circulation. 

condiments
grains and 

oils
fresh meat and seafood

household 
items

personal 
care 

products

books

bakery

entrance

rice and 
flour

 cooked 
food

Promotional

 items

frozen 
food

dried fruit

snacks

snacks

dairy 
products

bulk food

candy and 
chocolate

Promotional
 items

instant food

alcoholic and 
beverages

imported 
food

Checkout counter

 Supermarket Lockers

paper 
products

toys
stationery

kitchenw
are

vegetables
fruits

self-
scan
ning

self-
scan
ning

self-
scan
ning

N
on-Purchase E

xit

replenish
ment ports

 
Fig 5. New M Supermarket layout 

4. Evaluation of the Layout 
Optimization Effect of M 
Supermarket 

4.1. Determine the Evaluation Criteria 
Weights based on AHP 

A new layout plan has been developed for M Supermarket. 
To determine whether the new plan has advantages, the AHP-
FCE method will be used to evaluate both the new and old 
plans. 

4.1.1. Establish the Hierarchical Structure Model 
The hierarchical structure model for evaluating the layout 

of M Supermarket is divided into three levels: the goal level 
(optimal layout), the criteria level (evaluation impact 
indicators), and the alternatives level (new layout plan and old 
layout plan). Based on research of relevant references [11] 
and consultations with supermarket personnel, five evaluation 
impact indicators were identified: supermarket environment 
and convenience, replenishment convenience, layout 
scalability, supermarket operational efficiency, and 
operational costs. The hierarchical structure model for the 



 

230 

evaluation impact indicators of M Supermarket's layout is shown in Figure 6. 
 

Objective

Criterion

Optimal Layout

Supermarket 
Environment and 

Convenience

Convenience of 
Replenishment

Scalability of 
Layout

Supermarket 
Operational 
Efficiency

Operational 
Costs

New Plan Initial PlanPlan
 

Fig 6. Hierarchical Structure Model 
 

4.1.2. Constructing a Judgment Matrix  
The importance relationships and assigned values between 

each influencing factor were established through opinions 

gathered from specialized personnel responsible for internal 
layout, sales staff, and randomly interviewed customers. The 
constructed judgment matrix is shown in Table 4. 

 
Table 4. Judgment Matrix 

Indicators 
supermarket environment 

and convenience 
replenishment 
convenience

layout 
scalability

supermarket operational 
efficiency 

operational costs

supermarket environment 
and convenience 

1 2 3 
1
2

 
1
3

 

replenishment convenience 
1
2

 1 2 
1
3

 
1
6

 

layout scalability 
1
3

 
1
2

 1 
1
5

 
1
8

 

supermarket operational 
efficiency 

2 3 5 1 
1
2

 

operational costs 3 6 8 2 1 

4.1.3. Consistency Test and Calculation of Weights 
After obtaining the judgment matrix, the characteristic 

vector Wi is calculated using Formula 3. Then, the weight 
vector Wi

o is calculated using Formula 4. Once the 
characteristic vector and weight vector are determined, the λmi 
for each indicator is calculated using Formula 5. The specific 

data calculated is shown in Table 5 

Wi= ∏ a                 (3) 

Wi
o= 

∑
                   (4) 

	λ =
∑ 	

                (5) 

 
Table 5. Data for Characteristic Vector and Weight Vector 

Indicators 
supermarket 

environment and 
convenience

replenishment 
convenience 

layout 
scalability

supermarket 
operational 
efficiency

operational 
costs Wi Wi

o  

supermarket 
environment and 

convenience 
1 2 3 

1
2

 
1
3

 1.0000	 0.1489 5.0185

replenishment 
convenience 

1
2

 1 2 
1
3

 
1
6

 0.5610	 0.0835 5.0260

layout scalability 
1
3

 
1
2

 1 
1
5

 
1
8

 0.3342	 0.0497 5.0262

supermarket 
operational 
efficiency 

2 3 5 1 
1
2

 1.7188	 0.2559 5.0178

operational costs 3 6 8 2 1 3.1037 0.4620 5.0201

After obtaining the λmi for each indicator, the maximum 
characteristic root is calculated using Formula 

6( λ  =
. . . . .

 =5.0217). To 

measure the magnitude of C.I., the Random Index (R.I.) is 
introduced. According to Table 6, the corresponding R.I. 
value is found to be 1.12. According to Formula 7, the 

Consistency Index (C.I.) is 0.0054(C.I.=
.

 =0.0054). 

The Consistency Ratio (C.R.) is calculated using Formula 8. 
Since the calculated C.R. value is 0.0049, which is less than 

0.1, the consistency test is passed (C.R.= 
.

.
 

=0.0049<0.1). 
 

λ = ∑
∑ 	

                (6) 

C.I.=                    (7)  

C.R.= 
. .

. .
                    (8) 

 
 



 

231 

Table 6. Average Random Index of Consistency 
n 1 2 3 4 5 6 7 8 9 10 11 12 13 14

R.I. 0 0 0.52 0.89 1.12 1.26 1.36 1.41 1.46 1.49 1.52 1.54 1.56 1.58

After a one-time consistency test, the weight calculation 
results of the Analytic Hierarchy Process show that the weight 
score for Supermarket Environment and Convenience is 
0.1489, the weight score for Replenishment Convenience is 
0.0835, the weight score for Layout Scalability is 0.0497, the 
weight score for Supermarket Operational Efficiency is 
0.2559, and the weight score for Operational Costs is 0.462. 

4.2. Fuzzy Comprehensive Evaluation 
4.2.1. Establishing an Evaluation Matrix 

After obtaining the weights of each indicator, a set of 
factors U = {Supermarket Environment and Convenience, 
Replenishment Convenience, Layout Scalability, 

Supermarket Operational Efficiency, Operational Costs} is 
established based on the five indicators. Then, a set of 
judgment criteria V = {Excellent, Good, Moderate, Poor, 
Very Poor} is established, and each evaluation criterion is 
assigned a value. "Excellent" represents 10 points, "Good" 
represents 8 points, "Moderate" represents 6 points, "Poor" 
represents 4 points, and "Very Poor" represents 2 points. 

After setting up the factor set and the criterion set, in-depth 
interviews were conducted with ten experienced supermarket 
staff and layout personnel. They were asked to evaluate the 
new and old layout plans based on the five evaluation 
indicators. The specific evaluation results are shown in Table 
7 and Table 8. 

 
Table 7. Evaluation of New Layout Plan 

Evaluation of the New Layout Plan
Indicators Excellent Good Moderate Poor Very Poor

Supermarket environment and convenience 0.6 0.2 0.2 0 0 

replenishment convenience 0.7 0.2 0.1 0 0 

layout scalability 0.5 0.2 0.1 0.2 0 

supermarket operational efficiency 0.6 0.3 0.1 0 0 

operational costs 0.7 0.1 0.1 0.1 0 

Table 8. Evaluation of Initial Layout Plan 
Evaluation of the Initial Layout Plan

Indicators Excellent Good Moderate Poor Very Poor
Supermarket enviro- 

nment and convenience
0.2 0 0.4 0.2 0.2 

replenishment convenience 0.2 0.1 0.2 0.3 0.2
layout scalability 0.2 0.1 0.4 0.3 0

supermarket operational efficiency 0.3 0.2 0.5 0 0 
operational costs 0 0 0.4 0.3 0.3

Organizing the data, the evaluation matrices for the new 
and old plans are as follows: 

Evaluation Matrix R1 for New Plan 

A=

0.6 0.2 0.2 0 0
0.7 0.2 0.1 0 0
0.5 0.2 0.1 0.2 0
0.6 0.3 0.1 0 0
0.7 0.1 0.1 0.1 0

 

Evaluation Matrix R2 for Initial Plan 

B=

0.2 0 0.4 0.2 0.2
0.2 0.1 0.2 0.3 0.2
0.2 0.1 0.4 0.3 0
0.3 0.2 0.5 0 0
0 0 0.4 0.3 0.3

 

4.2.2. Performing Fuzzy Comprehensive Evaluation 
There are four commonly used fuzzy aggregation operators, 

as shown in Table 9. For comparing the comprehensive 
evaluation of plans, adopting the weighted average operator 
can more effectively reflect the effects of weights and expert 
evaluations. 

 
Table 9. Commonly used fuzzy aggregation operators  

Characteristics 
Operators

M (Λ, V) M (*, V) M (Λ, +) M (*,+) 

Type 
Dominant Factor 

Determination Type 
Dominant Factor 

Highlighting Type
Take Minimum and 

Bounded Type 
Weighted Average 

Type
Reflecting Weight 

Influence 
Not Apparent Apparent Not Apparent Apparent 

Degree of Aggregation Weak Weak Strong Strong 
Utilization of Evaluation 

Information 
Insufficient Insufficient Comparatively Sufficient Sufficient 

Weight sets for each indicator on layout plans: A = {0.1489, 
0.0835, 0.0497, 0.2559, 0.462}. Obtaining the fuzzy 
conclusion evaluation sets for the new and initial 

layout plans according to Formula 9. 

B=A*R                     (9) 
The fuzzy conclusion evaluation set for the new plan A is 

denoted as B1 = A * R1 
=[0.1489, 0.0835, 0.0497, 0.2559, 



 

232 

0.4620]*

0.6 0.2 0.2 0 0
0.7 0.2 0.1 0 0
0.5 0.2 0.1 0.2 0
0.6 0.3 0.1 0 0
0.7 0.1 0.1 0.1 0

 

=[0.6496,0.1794,0.1149,0.0561,0] 
The fuzzy conclusion evaluation set for the initial plan B is 

denoted as B2 = A * R2 
=[0.1489, 0.0835, 0.0497, 0.2559, 

0.4620]*

0.2 0 0.4 0.2 0.2
0.2 0.1 0.2 0.3 0.2
0.2 0.1 0.4 0.3 0
0.3 0.2 0.5 0 0
0 0 0.4 0.3 0.3

 

=[0.1332, 0.0645, 0.4089, 0.2083, 0.1851] 
After obtaining the fuzzy conclusion evaluation sets for the 

new and old plans, combined with the assigned judgment 
criterion set V = {10, 8, 6, 4, 2}, the comprehensive scores for 
the new and old plans can be derived. The comprehensive 
score for the new plan A is 8.84482, and for the initial plan B 
is 5.50476. Therefore, it can be seen that the new layout plan 
is more advantageous compared to the initial layout plan of 
the supermarket. 

5. Conclusion 
This study focuses on M supermarket, employing an 

improved SLP method tailored to its specific characteristics, 
substituting customer flow for goods flow to determine 
logistics relationships. Quantified data, combined with 
weighted calculations, determine the comprehensive 
relationship scores, and facilitate the creation of relevant 
diagrams and new layout plans. Five indicators were 
established to validate the advantages of the new plan, with 
AHP employed to determine weights. Experts were invited to 
score and establish evaluation matrices, ultimately 
confirming the superiority of the new plan. However, the 
study still has limitations, including a limited sample size 
affecting data representativeness, potential observation errors 
influencing the accuracy of customer flow calculations, 
expert scoring being subject to subjective and professional 

factors, and the new layout not considering issues such as cost 
and difficulty. 

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