Distribution Center Research Articles

The role of distribution centres in the logistics infrastructure of Kazakhstan

Distribution centres play a key role in the supply chain and their insufficient number will entail supply chain disruptions —supply delays and problems, as well as lost profits. Currently, distribution centres in Kazakhstan are located only in large cities. However, the growth of e-commerce (from 11729.9 billion tenge to 15763.7 billion tenge in 2022 compared to 2020) determines the need to solve this problem. Our study establishes the dependence between the areas of distribution centres and the e-commerce volume. This analysis, unlike the existing ones, examines the effect of the growth of e-commerce volumes on the increasing number of distribution centres as a prerequisite for the development of the logistics infrastructure of Kazakhstan against the background of the increase in the volume of goods supplied from China in transit to Europe. The aim of the study was to analyse the role of distribution centres in the logistics infrastructure of Kazakhstan. We justify the need to increase the number of distribution centres due to the increase in both turnover in goods transit, wholesale, and retail trade. The introduction of distribution centres ensures the continuous movement of goods and strengthens the connection between suppliers and consumers. The emergence of new technologies and innovations, combined with favourable market conditions and political support, creates favourable conditions for the development of reliable distribution centres that can improve logistics efficiency and contribute to the overall economic development of Kazakhstan.

중대재해처벌법 시행에 따른 물류사업장 내 안전의식수준 차이에 대한 연구

Purpose: This study examines whether the rise in logistics safety incidents has led to changes in workers’ safety awareness levels in distribution centers. Research design, data, and methodology: A t-test determined if there were changes in the safety awareness levels of managers and workers, analyzed by year and workplace. Results: The level of safety consciousness in the workplace and the level of safety consciousness in managers and workers according to the year, all showed significant differences. In addition, depending on the type of workplace, only the safety consciousness levels of managers showed significant differences between the groups. Conclusions: This study reviewed empirical analysis of the levels of awareness about logistics safety (in workplaces, managers, and workers) and presents theoretical conclusions and practical implications.

Location selection for logistics centre using PROMETHEE method

Logistics and distribution centres are essential to the supply chains of many manufacturing and logistics companies. Efficiently locating logistic centres involves thorough search for optimal place, prioritizing proximity to suppliers and minimizing costs. Companies’ management often solves the location problem of new halls, mostly to minimise the associated costs. Such a problem is solved in the automotive industry as part of the launch of a new international project. The key factor for the decision of where to locate the logistics centre is the location of the suppliers, since material deliveries generate a large part of the project costs. The aim of this study is to define a methodology for the location of the logistics centre, considering several alternative locations and relevant criteria. The location alternatives and criteria are defined in terms of minimising project costs and sustainability elements. The problem is solved using the multi-criteria decision-making approach. First, the AHP method is used to assign weights to the criteria. Then the PROMETHEE method is applied to find a suitable location for the logistics centre and to perform a thorough sensitivity analysis. The sensitivity analysis is focused on the impact of values of weights on the solution. Consequently, the analysis proves the correctness of the selected alternative. Based on the case study, a general methodology for locating a logistics centre is proposed.

Exploring the Coordination of Park Green Spaces and Urban Functional Areas through Multi-Source Data: A Spatial Analysis in Fuzhou, China

The coordinated development of park green spaces (PGS)with urban functional areas (UFA) has a direct impact on the operational efficiency of cities and the quality of life of residents. Therefore, an in-depth exploration of the coupling patterns and influencing factors between PGS and UFA is fundamental for efficient collaboration and the creation of high-quality living environments. This study focuses on the street units of Fuzhou’s central urban area, utilizing multi-source data such as land use, points of interest (POI), and OpenStreetMap (OSM) methods, including kernel density analysis, standard deviational ellipse, coupling coordination degree model, and geographical detectors, are employed to systematically analyze the spatial distribution patterns of PGS and UFA, as well as their coupling coordination relationships. The findings reveal that (1) both PGS and various UFA have higher densities in the city center, with a concentric decrease towards the periphery. PGS are primarily concentrated in the city center, exhibiting a monocentric distribution, while UFA display planar, polycentric, or axial distribution patterns. (2) The spatial distribution centers of both PGS and UFA are skewed towards the southwest of the city center, with PGS being relatively evenly distributed and showing minimal deviation from UFA. (3) The dominant type of coupling coordination between PGS and various UFA is “Close to dissonance”, displaying a spatial pattern of “high in the center, low on the east-west and north-south wings”. Socioeconomic factors are the primary driving force influencing the coupling coordination degree, while population and transportation conditions are secondary factors. This research provides a scientific basis for urban planning and assists planners in more precisely coordinating the development of parks, green spaces, and various functional spaces in urban spatial layouts, thereby promoting sustainable urban development.

Correlation of Plantation Area and Palm Oil Production in Sumatra and Kalimantan Regions

This study aims to analyze the correlation between the area of oil palm plantations and oil palm production in Indonesia, especially in the Sumatra and Kalimantan regions which are the centers of oil palm plantation distribution. Data collection using secondary data from the Central Statistics Agency (BPS), this study aims to determine the relationship between the increase in land area and oil palm plantation production over the past 10 years. This study uses a quantitative method with a correlative approach. Data analysis was carried out using a bivariate correlation Pearson correlation test to determine the positive relationship between plantation area and oil palm production. The results of the analysis showed a significant positive relationship between the land area variable and oil palm production in both the Sumatra and Kalimantan regions, this is indicated by a positive number and a strong correlation of 0.852 for the Sumatra region and very strong, namely 0.996 for the Kalimantan region. In addition, the results of the interpretation of the correlation by looking at Sig. (2-tailed) also show that between the land area variable and production there is a significant correlation, namely 0.002 for the Sumatra region and a value of 0.000 for the Kalimantan region. Although the correlation between land area and production shows a positive value and has a very strong correlation, there are still other factors such as technology, climate, and management practices that also play a role in influencing palm oil production results.

Forecasting Appropriate Habitats for Rare and Endangered Indocalamus Species in China in Response to Climate Change

China’s rare and endangered bamboo species belonging to the Indocalamus genus, specifically Indocalamus decorus Q. H. Dai, Indocalamus hirsutissimus Z. P. Wang & P. X. Zhang, and Indocalamus pedalis (Keng) P. C. Keng, possess notable value in biodiversity conservation and have significant potential for use in landscape design. Using an enhanced MaxEnt model, this study forecasted shifts in the species’ potential range under four separate climate scenarios (SSP1-RCP2.6, SSP2-RCP4.5, SSP3-RCP7.0, and SSP5-RCP8.5), considering both the historical period (1970–2000, referred to as “the current period”) and upcoming timeframes (2021–2040, 2041–2060, 2061–2080, and 2081–2100). The analysis disclosed that the present total potential habitat area for these species is approximately 251.79 × 104 km2, with high, medium, and low suitability areas occupying 0.15 × 104 km2, 125.39 × 104 km2, and 126.26 × 104 km2, respectively. The minimum temperature of the coldest month emerged as the critical determinant of their potential habitat distribution. Expected climate changes are likely to increase the suitable habitat for these species, although areas with low suitability might slightly diminish, with Guizhou and Chongqing showing the least impact. The distribution centers of suitable habitats for the three plant species consistently exhibit a westward shift under various climate scenarios. These results contribute valuable insights for the spatial distribution, continuous monitoring, sustainable management, and ex situ conservation in response to climate change.

Factor Affecting Work Efficiency of Pick Tower Department Employees in Lotus Distribution Center, Khon Kaen, Thailand

The purpose of this study is to Factor Affecting Work Efficiency of Pick Tower Department Employees in Lotus Distribution Center Khon Kaen. The Sample is Pick Tower Department Employees in Lotus Distribution Center, Khon Kaen. The instrument used was a questionnaire consisting of 80 people by accidental sampling. The average of Item-Objective Congruence Index (IOC) was 0.78 and the Reliability index was 0.83. The statistics used for data analysis were percentage, mean, standard deviation and Stepwise Multiple Regression statistics. The findings disclosed as follows: (1) Motivating elements in terms of job responsibilities, supervisors grant employees autonomy and confidence in carrying out their duties, which has an impact on work productivity. (2) The policy and administration supporting factors consist of an organization-wide executive meeting where policies and work practices are explained, as well as employee participation in operation planning. With respect to the conditions of employment, A secure workplace exists. Orderly and orderly Convenient for business Having adequate and suitable equipment required to perform the task will have an impact on the task's efficacy with the significance level .05.

Enhancing supply chain resilience through risk mitigation strategies: Evidence from smallholder red chili supply chains in East Java Indonesia

The cultivation of red chili in East Java, Indonesia, has significant economic and social impacts, necessitating proactive supply chain measures. This research aimed to identify priority risk agents, develop effective risk mitigation, and enhance supply chain resilience using the SCOR model, House of Risk, Interpretative Structural Modelling (ISM), and synthesis analysis. Examining 238 respondents—including farmers, collectors, wholesalers, retailers, home-agroindustries, and experts—the findings highlight farmers’ critical role in supply chain resilience despite risks from crop failures, weather fluctuations, and pest infestations. Simultaneous planting led to market oversupply and price drops, but accurate pricing information facilitated quick market adaptation. Wholesalers influenced pricing dynamics and income levels, impacting farmers directly. To improve resilience, three main strategies were developed through ten key elements: proactive strategies (real-time SCM tracking, Weather Early Warning Systems, risk management team formation, and training), resistance strategies (partnerships, chili stock reserves, storage and drying technologies, GAP implementation, post-harvest management, agricultural insurance, and Fair Profit Sharing Agreements), and recovery and growth strategies (flexible distribution channels and customizable distribution centers). Furthermore, the study delves into the mediating and moderating effects between variables within the model. This research not only addresses a knowledge gap but also provides stakeholders with evidence to consider new strategies to enhance red chili supply resilience.

From Single Orders to Batches: A Sensitivity Analysis of Warehouse Picking Efficiency

Currently, companies are called to meet variable market demand whilst having to comply with tighter delivery times, also due to the growing spread of e-commerce systems in the last decade. As never before, it is therefore mandatory to increase the efficiency within distribution centers to minimize operating costs and increase environmental and economical sustainability. The picking process is the most expensive task in a warehouse, both for the required resources and time for completing all the operations, which is typically carried out manually. Several policies can be identified, such as discrete or batch picking. Many studies tend to optimize both policies, treating them distinctly and integrating them with other factors including, for instance, the logic of product allocation. This article stands on a higher decision-making level: starting from a database obtained with a simulative approach that contains the average distances covered by pickers in different warehouse configurations, the aim is to provide an analysis of which factors have the greatest impact in preferring a discrete order picking policy over the batch one. The factors in question are shape factor, input–output point, routing and storage location assignment policies. Results can be useful for industrial practitioners in defining the most efficient managerial strategies.

Additional criteria on scintigraphic testing for diagnosis of rapid colonic transit in patients with chronic diarrhea.

Colonic transit (CT) measured by validated scintigraphy using 111In-labeled activated charcoal particles is summarized using geometric center (GC) of isotopic distribution in four colonic regions and stool at 24 and 48 h. Diagnosis of rapid CT is currently based on GC24 ≥4.4 in females and >4.7 in males, which lack sensitivity. Our aim was to evaluate, in patients with chronic diarrhea with normal CT by GC24 and GC48, the diagnostic utility of CT change (∆GC) relative to sex-matched normal values. We evaluated two adult patient cohorts: 701 clinical patients (1994-2023) with chronic diarrhea and 76 research participants with irritable bowel syndrome with diarrhea (N = 63) or bile acid diarrhea (BAD, N = 13). Results of ∆GC were compared to 220 healthy controls' 95th percentiles (%ile) (≥2.0 females and ≥2.2 males). In the research cohort, we also analyzed (Spearman correlation) colonic ∆GC with ascending colon emptying T1/2 (AC T1/2), average stool frequency and consistency based on a daily diary, total fecal bile acid (BA) concentration, and % primary BA in a single stool sample. Among 701 clinical patients with normal GC24, 160 (22.3%) had rapid CT based on ∆GC 95th %ile in health. Among 76 research participants, an additional 20.6% IBS-D and 23% BAD had rapid CT ∆GC. Younger age and absence of diabetes mellitus were predictive of rapid ∆GC. ∆GC significantly correlated with AC T1/2 and with fecal BA. ∆GC identified an additional 21%-23% patients with rapid colonic transit among patients with diarrhea and normal GC24.

An artificial bee colony optimization algorithms for solving fuzzy capacitated logistic distribution center problem

This paper presents a methodological approach to solving the fuzzy capacitated logistic distribution center problem, with a focus on the optimal selection of distribution centers to meet the demands of multiple plants. The distribution centers are characterized by fixed costs and capacities, while plant demands are modeled using fuzzy triangular membership functions. The problem is mathematically formulated by converting fuzzy demands into crisp values, providing a structured framework for addressing uncertainty in logistic planning. To support future research and facilitate comparative analysis, 20 benchmark problems were generated, filling a gap in the existing literature. Three distinct artificial bee colony algorithm variants were hybridized with a heuristic: one using the best solution per iteration, another incorporating chaotic mapping and adaptive procedures, and the third employing convergence and diversity archives. An experimental design based on Taguchi's orthogonal arrays was employed for optimizing the algorithm parameters, ensuring systematic exploration of the solution space. The developed methods offer a comprehensive toolkit for addressing complex, uncertain demands in logistic distribution, with code provided for reproducibility.Key contributions include:•Development of a fuzzy model for the selection of distribution centers with fixed costs and capacities under uncertain plant demands.•Generation of 20 benchmark problems to advance research in the fuzzy capacitated logistic distribution center problem domain.•Integration of a heuristic approach with three distinct ABC algorithm variants, each contributing unique methodological insights.

Motivation and retention of outsourced employees

ABSTRACT A food service supplier is experiencing that, in their distribution centres, within 30 days, an average of 48% of the outsourced employees resign, which impacts profitability, productivity and service quality. This study investigates which factors of the Herzberg two-factor motivation theory contribute to the retention of outsourced employees of a food service supplier and whether there is a difference between eastern or southern European employees. A total of 299 outsourced employees of the food service suppliers at four out of nine distribution centres filled out a 15-item survey, including questions on the various aspects of the Herzberg motivation theory, and their intention to stay with the company. Results show that extrinsic motivation factors play a more significant role in the retention of outsourced employees in comparison to the intrinsic factors. Extrinsic factors significantly correlated with retention are policies and administration, work conditions, supervision and interpersonal relations. Intrinsic factors significantly correlated with retention are advancement, the work itself and achievement. No significant relationship was found between the salary factor and employee retention. Although results showed that southern Europeans tend to stay longer with the company in comparison to eastern Europeans, no significant differences were observed regarding the impact of motivation and hygiene factors between the two sub-groups. To enhance retention, the food service supplier is advised to provide sufficient growth and development opportunities, assign important responsibilities and acknowledge accomplishments. Furthermore, the company must assess, track and oversee all relevant extrinsic and intrinsic motivation factors to connect the outsourced employees with the company for a longer term.

Urea Concentration Detection in Milk Using Microscopic Image Processing Algorithm under Ultraviolet Light Approach

The adulteration of milk is a pressing concern for the citizens of India and people all around the globe. Due to a lack of regulation compliance and insufficient surveillance infrastructure, it is noticeably worse in emerging and slow-growing nations. One of the most common and dangerous adulterants in milk is urea. If the permissible quantity of urea in milk is surpassed, it could have a major negative impact on people's health. All existing methods of urea detection require time, expertise, costly chemicals, and enzymes, along with exorbitant instruments and instrument-specific expertise. The key to overcoming this challenge is having the infrastructure to detect adulterated milk. This study aims to identify a cost- effective and largely implementable system for quantitative detection of urea content to identify adulterated milk primarily for milk distribution centers in India. The proposed milk adulteration detection system, dubbed the MADS, entails a cost-effective, rapid, accurate, precise, and completely novel method for the quantitative computation of urea levels in adulterated milk. It is a device that detects the concentration of particles of urea in milk using a microscopic image processing algorithm under ultraviolet light. Using ultraviolet light and a proprietary program in Python, the isolation of the urea particle from the rest of the milk solids is done and the area concentration, as an average of the value calculated in each of the frames of the video captured through the microscopic camera, is computed. This gives the final urea concentration in milk, which can be used to check whether the concentration follows the government guidelines and exceeds the legal limit.

Integrating storage allocation with manual order picking and replenishment operations in a distribution centre

ABSTRACT This paper introduces a mathematical programming formulation and a simulation-based heuristic for the allocation of storage positions to products picked by human operators on man-aboard vehicles traveling through the warehouse of a wholesale company. In this problem, the tactical level of the assignment decisions affects the operational level of the picking process. We propose a simulation-optimisation framework that integrates the two. Our formulation of the storage location assignment problem also handles the constraint according to which a picking position should be paired with a (vertical) replenishment position for a given item. To solve realistic instances, we design an iterated local search (ILS) metaheuristic with an embedded discrete-event simulator (DES) that evaluates the most promising moves at each iteration. The DES allows reproducing the handling operations performed by multiple order pickers under uncertainty, mutual interferences and congestion-related phenomena. Overall, the flexible simulation-optimisation (SO) framework evaluates the operational times and daily productivity of the order picking organisation. Numerical results are presented for real data, under an S-shape picking policy with a skip-and-go rule to deal with lacking items. Under a proper tuning of the ILS parameters, the SO framework allows to achieve a nearly 17% improvement in warehouse productivity.

Designing a new sustainable healthcare network considering the COVID-19 pandemic: Artificial intelligence-based solutions

The COVID-19 pandemic, which is still spreading its new mutations all around the world, is considered a healthcare challenge around the world. The best approach to forestall this pandemic is to avoid exposure to the virus. Therefore, medical protective equipment is essential for fighting this pandemic. This underlines the chief role of having a sustainable supply chain network (SCN) for producing and distributing personal protective equipment to avoid shortage and augmenting costs. The reality, however, is that the COVID-19 pandemic leads to many developments in countries and this study is another step for these purposes. This research developsa multi-period, multi-objective, multi-echelon, and multi-product medical protective equipment sustainable SCN considering the production, distribution, allocation, and inventory with “risk pooling” strategy effect with the aim of filling the existing gaps in health SCN research during the COVID-19 pandemic. By applying the risk pooling strategy, lower inventory levels or higher service levels can be achieved without increasing inventory costs. This model explores the possibility of lateral transshipments between distribution centers, as a way to increase the reliability of SCN performance. We model a new production, inventory, distribution, location, and allocation problem and consider four objectives for our suggested model (i) minimizing total SCN costs, (ii) minimizing environmental effects, (iii) minimizing social impacts, and (iv) maximizing the reliability of demand delivery. The proposedmodel simultaneously examines all three dimensions of sustainability (economic, environmental, and social) as well as the reliability of demand delivery. Considering all of these decisions and assumptions brings the studied problem closer to reality. We employ various algorithms for solving our developed model with different sizes: the improved version of the augmented ε-constraint (AUGMECON2) algorithm for small and medium-sized problems and two meta-heuristic algorithms, i.e., Multi-Objective Whale Optimization Algorithm (MOWOA) and Multi-Objective Variable Neighborhood Search (MOVNS) algorithm, for large-sized ones. The Taguchi approach is used to tune the parameters of meta-heuristic algorithms, and a comparison is performed using four evaluation metrics: Mean Ideal Distance (MID), Number of Pareto Solutions (NPS), Maximum Spread (MS), and Spread of Non-Dominance Solution (SNS). Proposed solving methods for the studied problem and making comparisons between them are another innovation of this study. A couple of numerical examples are provided to illustrate the applicability of the presented solution methods. Finally, sensitivity analysis for problem parameters is performed to validate our suggested model. Our study reveals the superiority of the MOWOA over the other algorithms.

A distributed auditory network mediated by pontine central gray underlies ultra-fast awakening in response to alerting sounds

Sleeping animals can be woken up rapidly by external threat signals, which is an essential defense mechanism for survival. However, neuronal circuits underlying the fast transmission of sensory signals for this process remain unclear. Here, we report in mice that alerting sound can induce rapid awakening within hundreds of milliseconds and that glutamatergic neurons in the pontine central gray (PCG) play an important role in this process. These neurons exhibit higher sensitivity to auditory stimuli in sleep than wakefulness. Suppressing these neurons results in reduced sound-induced awakening and increased sleep in intrinsic sleep/wake cycles, whereas their activation induces ultra-fast awakening from sleep and accelerates awakening from anesthesia. Additionally, the sound-induced awakening can be attributed to the propagation of auditory signals from the PCG to multiple arousal-related regions, including the mediodorsal thalamus, lateral hypothalamus, and ventral tegmental area. Thus, the PCG serves as an essential distribution center to orchestrate a global auditory network to promote rapid awakening.

A multi-level multi-product supply chain network design of vegetables products considering costs of quality: A case study.

Effective logistics management is crucial for the distribution of perishable agricultural products to ensure they reach customers in high-quality condition. This research examines an integrated, multi-echelon supply chain for perishable agricultural goods. The supply chain consists of four stages: supply, processing, storage, and customers. This study investigates the quality-related costs associated with product perishability to maximize supply chain profitability. Key factors considered include the network design, location of processing and distribution centers, the ability to process raw products to minimize post-harvest quality degradation, the option to sell the excess produce to a secondary market due to unpredictable yields, and the decision not to fulfill demand from distant customers where significant quality loss and price drops would be involved, instead diverting those products to the aforementioned secondary market. Quantitative methods and linear mathematical programming are employed to model and validate the proposed supply chain using actual data from a real-world case study on vegetable supply chains. The main contribution of this research is the incorporation of quality costs into the objective function, which allows the supply chain to prioritize meeting nearby customers' demands with minimal quality loss over serving distant customers where high quality loss is unavoidable. Additionally, deploying a faster transportation fleet can significantly improve the overall profitability of the perishable product supply chain.

Inclusion Strategy for Constructing S/N Orbital Hybridization-Regulated sp3/sp2 Carbon toward Boost Electrocatalysis.

Metal-free carbon-based electrocatalysts have gained significant attention in the field of zinc-air batteries (ZABs) due to their affordability, good conductivity and chemical stability. However, unmodified carbon materials typically fall short in adsorbing and activating the substrates and intermediates involved in oxygen reduction reactions (ORR). Here, a metal-free carbon-based electrocatalyst with S atom p orbital hybrid modified N-sp3/sp2 carbon structure (C/NS) were prepared by cyclodextrins inclusion. The catalyst demonstrates impressive ORR activity (E1/2=0.885 V vs. RHE) and robust ZABs performance with a power density of 171.3 mW cm-2 and a specific capacity of 781.2 mAh g-1. Density functional theory (DFT) calculation reveals that S atom effectively regulates the charge distribution and p-band center of active site carbon atom in the N-sp3/sp2 carbon structure. This modification prompts the adsorption and dissociation of O2 and intermediates, resulting in higher reactive activity. This work provides a valuable and practical strategy for preparing cost-effective metal-free carbon-based electrocatalysts for ORR with high performance.

Geographic distribution and impacts of climate change on the suitable habitats of two alpine Rhododendron in Southwest China

Mountains of Southwest China (MSC) serve as a prominent geographical distribution center for Rhododendron delavayi and Rhododendron irroratum (Ericaceae). These mountains are currently experiencing an unparalleled warming trend, which poses severe challenges to the survival of these keystone alpine Rhododendron species. However, the geographical distribution responses of these species to climate change remain incompletely understood and are often overlooked. Here, we constructed ensemble models (EMs) using ten models of five algorithms to calibrate ecological niche models and predict suitable habitat areas for the two Rhododendron species across four climate emission scenarios over three distinct periods. Our analysis indicated the higher importance of elevation than temperature and precipitation in shaping the spatial distribution of the two alpine Rhododendron species. The current suitable habitats of R. delavayi and R. irroratum have areas spanning 14.85 × 104 and 11.01 × 104 km2, respectively, which are mostly distributed in the western and central regions of MSC. The suitable habitat of R. delavayi is projected to decrease by 15.09–75.31 %, but the potential habitat of R. irroratum is expected to shrink by12.71 % to 76.8 % in different future climate scenarios. The suitable habitats of these species may become confined in a “summit trap” within relatively low-altitude regions, whereas habitats distributed at high altitudes may serve as “biological refuges.” The future distribution of the two alpine Rhododendron species will shift to high altitudes in westward and northward regions, with substantial thermal and hydrothermal changes as the primary drivers of habitat alteration and migration patterns. The losses or benefits for species under climate warming depend on their ecological niches and geographical location, which provide a geographical guidance for the long-term conservation and sustainable use of species and essential insights into the spatial conservation assessment of alpine plant groups in biodiversity hotspots in the future.

Optimising picking operations in distribution centres: a simulation and algorithm-based approach for travel distance reduction

Abstract This study examines the pivotal role of the logistics sector in corporations, particularly those with diverse product portfolios. It focuses on the time-intensive “picking” process, driven by various products and material handling requirements for order fulfilment. The research presents a methodology that combines distribution centre modelling for simulation with an optimisation algorithm to enhance operational efficiency. The goal is to determine an optimal route for product retrieval, minimising employee travel distances, using the simulated annealing algorithm. The results showcase a significant 7 % reduction in employee travel distance during collection. This research is relevant to academia and practical applications as it presents an opportunity to reduce operational costs in distribution centres, enhance the efficiency of picking operations, and improve the competitiveness of companies. Furthermore, it contributes to operations research by addressing a complex problem with significant practical implications using a rather unused method to solve this problem of picking operations. The approach is empirically applied in a prominent Brazilian beverage company. This methodology proves valuable for optimising logistics operations in various industrial contexts, highlighting its practical applicability.