Browsing by Author "Gökçe, Mahmut Ali"

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Assembly Line and Workload Balancing with Competency-Based Worker Assignment in Apparel Production
(Springer Science and Business Media Deutschland GmbH, 2023) Yiğit Efe Bilir; Benay Dişbudak; Oğuzhan Aydın; Emre Demirhisar; Burçak Sena Koçak; Yusuf Durğay; Selen Burçak Akkaya; Mahmut Ali Gökçe; Gökçe, Mahmut Ali; Durğay, Yusuf; Aydın, Oğuzhan; Dişbudak, Benay; Demirhisar, Emre; Bilir, Yiğit Efe; Koçak, Burçak Sena; N.M. Durakbasa , M.G. Gençyılmaz
The apparel industry is challenging for production management due to rapid changes in fashion. Accordingly customer needs and expectations increase constantly. As a result apparel factories must be able to increase production rate efficiency and quality in order to survive in this dynamic world. To this end assembly line balancing which affects the overall cost and efficiency in apparel industry plays a critical role. In this study real-life assembly line balancing and competency-based worker assignment problems in apparel industry sewing workshop are examined simultaneously and implementation at a big apparel company is presented. A novel mathematical model is proposed to solve this integrated problem. Operation-worker and operation-workstation assignments are made for a given number of workstations operations and workers. The competency score of the worker on each machine type is a key factor in determining worker-operation assignment. Assignments are made in such a way that the total competency score of the line must exceed a pre-specified limit. The objective is to minimize the workload difference between workers on the assembly line for a given cycle time limit. The proposed model is solved using Google OR-Tools and is verified using real-life data from the company. Since the competency of the workers is crucial in operations based on manual labor the proposed model can also be adapted to many industries in addition to the apparel industry. © 2024 Elsevier B.V. All rights reserved.
Bağlantılı sinyalize dönel kavşaklar için sinyal sürelerinin optimizasyonu
(2022) Qadri, Syed Shah Sultan Mohiuddin; Gökçe, Mahmut Ali; Öner, Erdinç
Managing high traffic volumes and mitigating traffic congestion including slow-moving traffic at intersections from the urban traffic networks is the key challenge for urban administration. The increase in the number of vehicles on a daily basis in the urban network is causing a continuous deterioration in the traffic situation. This deterioration leads to many detrimental consequences on health, the economy, and the environment. Due to this, it is important to manage the flow of vehicles within these networks efficiently. As an effective intersection design, the roundabout is rapidly gaining attention and popularity among traffic engineers because of its capacity for the mobility of the number of vehicles. This capacity can further be improved through their signalization. The appropriate traffic signal timing concerning the traffic conditions is critical in providing smooth traffic flow. Inappropriate traffic signal timings not only cause delays and inconvenience to drivers but also increase environmental pollution due to excessive fuel consumption and the emission of greenhouse gases. Thus, it is important to investigate the different signal timings to ensure that implemented plan will improve the capacity and the performance of the network. The investigation can be conducted via either field testing or the use of a reliable simulation tool. As the microscopic simulation is safer, less expensive, and faster than field implementation and testing, which is why the simulation models are widely used in both transportation operations and management analysis. Many researchers have made an effort to improve the efficiency of traffic signals using different approaches. However, few studies have been done concerning traffic signal timings at roundabouts. Roundabouts have a different flow dynamic compared to regular intersections. With the increasing use of signalized roundabouts, especially in metropolitan areas, the traffic signal timings of roundabouts need to be studied. This dissertation introduces a simulation-based optimization framework for finding the optimal green phase timings of signal heads located at an isolated and a network of connected signalized roundabouts. In the developed framework, SUMO is used as a simulation tool whereas the genetic algorithm is used as an optimization algorithm. Two realistic simulation models for the roundabouts (isolated and the network) located in downtown Izmir, Turkey are also developed in order to test the frameworks' performances. The results of the proposed frameworks have been compared with the current settings and with Webster's results. It was found the proposed framework outperforms both the current settings and Webster in all performance measures that are outlined in this study.
Development of Simulation-Based Framework to Evaluate Urban Delivery Policies Using Electric Scooters
(2025) Rala, Zeynep; Gökçe, Mahmut Ali
The process of order delivery has become very important as part of urban logistics operations with the rapid increase in electronic commerce (e-commerce). Efficiency of processing and delivery of online orders is crucial for customer satisfaction and viability of the business. Also, solutions are needed for decreasing the carbon footprint of this delivery operations for sustainability reasons. This study presents a simulation-based framework that enables evaluation of different policies for online order processing and delivery in an urban setting utilizing electric scooters with swappable batteries as a sustainable alternative to fossil fuel-powered counterparts under realistic conditions. There is also a detailed computational study. The results from an experimental design using a data set with order arrival times, delivery locations, and the weight and size of packages are also presented. Factor considered for policies include order grouping by location and arrival time, courier routing, and battery swapping rules. The model also highlights the impact of integrating electric vehicles (EVs) into urban logistics by reducing emissions and noise, improving efficiency, and enhancing customer satisfaction. This research offers a comprehensive framework for sustainable delivery that optimizes both operational and environmental performance.
Elektrikle çalışan sokak süpürücüleri için zaman pencereli ve ara duraklı ayrıt rotalama problemi
(2019) Yurtseven, Cansu; Gökçe, Mahmut Ali
Atık toplama belediye hizmetleri içinde yer alır. Atık toplama problemleri gerçek hayatın içinden ve etkileri yüksek olduğundan, son zamanlarda bu problemler daha fazla çalışılmaya başlanmıştır. Atık toplama hizmetlerinin, karşılığında gelir olmadığından, kamu fonları ile minimum maliyetle gerçekleştirilmesi önemlidir. Sokak süpürme işlemi, belediye hizmetleri arasında atık yönetimi açısından önemli bir yer tutar. Son zamanlarda, elektrikli sokak süpürücüler, enerji verimlilikleri ve çevre koruma nedenleriyle artan bir oranda tercih edilmeye başlanmıştır. Bu çalışmada, atık boşaltım operasyonu, araç şarj planlaması, öğle yemeği ve dinlenme molaları gibi gerçekçi operasyonel kısıtları göz önünde bulundurarak, şehirdeki önceden belirlenmiş bir dizi sokağa hizmet vermek için elektrikle çalışan sokak süpürücülerinin rotalarını belirleme sorunu ele alınmaktadır. Sokak süpürme hizmetini gerçekleştirmek için farklı kapasitelere ve batarya seviyelerine sahip elektrikle çalışan heterojen bir araç filosunu ele alarak, verilen zaman pencereleri içerisinde süpürülme ihtiyacı olan caddelerden atıkları toplamak için, süpürücülerinin optimal rotalarını belirlemek amacıyla, yeni bir matematiksel model önerilmektedir. Kullanılan araçların zaman periyodunun başlangıcında bir depodan çıkması ve gün sonunda tekrar depoya geri dönmesi planlanmaktadır. Enazlanan amaç fonksiyonu, hizmeti kısıtlara göre sağlarken, seyahat ve atık boşaltım işlemlerinde kullanılan enerji tüketimini en aza indirmektir. Matematiksel modelin performansını ölçmek için, gerçek hayat örnekleri ile bir vaka çalışması ve deney tasarımı yapılmış, deney sonuçları incelenmiştir.
Fuzzy TOPSIS and Goal Programming Approaches to Multi Objective Facility Location Problem for Emergency Goods and Services Distribution and Bornova/Izmir Case Study
(Springer Science and Business Media Deutschland GmbH, 2022) Mert Paldrak; Simge Güçlükol Ergin; Mahmut Ali Gökçe; Melis Tan Tacoglu; Gökçe, Mahmut Ali; Tan Tacoğlu, Melis; Paldrak, Mert; Güçlükol, Simge; Tacoglu, Melis Tan; C. Kahraman , S. Cevik Onar , B. Oztaysi , I.U. Sari , A.C. Tolga , S. Cebi
Distributions of vital goods and services in emergency or post disaster situations are of paramount importance to be able to meet the requirements of those in need on time. Finding an appropriate location for facilities to distribute such goods and services efficiently and quickly is an important challenge. In such a situation location decisions for these facilities must be made quickly considering multiple objectives. This problem is a multi-objective facility location problem (MOFLP). The main focus of this study is to present two solution methodologies for a MOFLP in a post disaster situation. We specifically consider objective of minimizing maximum weighted distance traveled and minimizing total cost of facilities to be opened in order to satisfy all demand. We also provide a version of the problem when the number of facilities to be opened is limited and second objective becomes maximizing demand covered. Due to the conflicting nature of the objective functions we propose to apply Fuzzy TOPSIS and Goal Programming and compare the solutions obtained using these two techniques with respect to solution quality and computational time. We present the developed models and provide results from a real-life application using existing emergency assembly areas and current census data for Bornova/İzmir. This paper contributes in two ways to existing literature. First is the comparison between multiple (two) solution methodologies for MOPLP. Studies in the literature provide only one solution technique such as Fuzzy TOPSIS Goal Programming etc. Secondly we implement these methodologies by using real life data for emergency situations. © 2022 Elsevier B.V. All rights reserved.
Citation - WoS: 1
Citation - Scopus: 1
Improving the Performance of a Network of Signalized Roundabouts via Microscopic Traffic Simulation Tool
(Springer Science and Business Media Deutschland GmbH, 2022) Syed Shah Sultan Mohiuddin Qadri; Mahmut Ali Gökçe; Erdinc Oner; Gökçe, Mahmut Ali; Qadri, Syed Shah Sultan Mohiuddin; Öner, Erdinç; C. Kahraman , S. Cevik Onar , B. Oztaysi , I.U. Sari , A.C. Tolga , S. Cebi
Roundabouts are effective intersection designs which are rapidly gaining attention and popularity among traffic engineers. This is due to the roundabout’s capacity to handle the mobility of a substantial number of vehicles. The ever increasing demand for more traffic capacity can be satisfied by either significant capital investment in infrastructure or creating more capacity by intelligent signalization. The appropriate traffic signal timing is critical in smoothing traffic flow. Inappropriate traffic signal timing not only causes delays and inconvenience to drivers but also increases environmental pollution. Thus it is important to investigate different signal timings to ensure that implemented plan will have a positive impact on the network’s performance. The optimization of roundabouts’ signal timing is relatively a new area of research. The problem is difficult to model realistically and computationally challenging. Due to the flow nature of the traffic problem wider areas of traffic must be regulated simultaneously in a network. This can be achieved via either field-testing or using a reliable simulation tool. Microscopic simulation allows a safer and cheaper evaluation of many more alternative signal timings compared to field-testing. Although development calibration and validation of simulation models for traffic networks are challenging. We present a model to evaluate the performance of a network of signalized roundabouts with which the combination of different traffic volume and cycle length scenarios can be intelligently studied. We also provide information on the development calibration and validation of the model as well as a real-life implementation on a network of roundabouts in Izmir/Turkey. © 2022 Elsevier B.V. All rights reserved.
Integrated Transportation and Packaging Problem Modeling and Application
(Springer Science and Business Media Deutschland GmbH, 2021) Tuğçe Köksal; Ege Akkuş; Gökçe Demirel; Esin Tosun; Mahmut Ali Gökçe; Cansu Yurtseven; Gökçe, Mahmut Ali; Demirel, Gökçe; Köksal, Tuğçe; Yurtseven, Cansu; Tosun, Esin; Akkuş, Ege; N.M. Durakbasa , M.G. Gençyılmaz
The Hybrid Flow Shop scheduling (HFSS) is a complex problem observed in many real-life problems and usually involves a work environment with multiple parallel machines at each stage. This study deals with a scheduling problem that integrates transportation and packaging operations. The problem originates from a real-life problem at a leading global rim manufacturing company headquartered in Turkey. We propose a novel solution method which is able to create a schedule for all stages while minimizing the total weighted earliness of orders. The studied problem differs from classical HFSS problem in a number of ways therefore an improved mathematical model to accommodate current problem and system constraints is developed. The new two-stage as Mixed-Integer Programming model (MIP) is constructed verified and validated. As the problem is NP-hard a novel rule-based heuristic algorithm for two stages is developed. The performances of the heuristic algorithm and the mathematical model are compared using real-life data from the company. Based on the results from the experimentation proposed heuristic algorithm performs very well in a significantly shorter computational time. Moreover a user-friendly decision support system (DSS) is created and both solution methods are embedded in this DSS for the implementation at the company. © 2020 Elsevier B.V. All rights reserved.
Citation - Scopus: 1
Matheuristic Algorithm for Automated Guided Vehicle (AGV) Assisted Intelligent Order Picking
(Springer Science and Business Media Deutschland GmbH, 2023) Simge Güçlükol Ergin; Mahmut Ali Gökçe; Gökçe, Mahmut Ali; Ergin, Simge Güçlükol; C. Kahraman , I.U. Sari , B. Oztaysi , S. Cevik Onar , S. Cebi , A.C. Tolga
Warehouse management plays an important role in the supply chain. It has received attention from academics and the industry for many years. During this time warehouse management processes have evolved like all other systems in the industry. Preparing orders faster has a key role for companies with an increasing demand from online shopping. The requirements for rapid response to customers have increased. Meanwhile the use of automated guided vehicles (AGVs) has increased because they are used to collect items by pickers in warehouses to prepare customer orders. Assignments of orders to AGVs and routing of AGVs should be done quickly and efficiently to prepare orders. Due to the NP-hardness of the problem it is difficult to solve realistic-size problems in an acceptable amount of time especially when orders from online shopping flow at a fast pace. In this study a new matheuristic algorithm was proposed to minimize the total traveled distance by all AGVs to collect orders with a minimum number of AGVs. This helps to reach a more sustainable system. Minimizing the distance of all AGVs helps for rapid responses to customers’ orders with minimum total energy/cost. Experimental results were provided to compare the computational complexities and performances of the models in this paper. The proposed novel matheuristic algorithm was shown to create intelligent order picking operations in warehouses within a reasonable computational time. © 2023 Elsevier B.V. All rights reserved.
Citation - Scopus: 1
Multi Model Multiple Line Balancing Problem Modeling and Real-Life Application
(Springer Science and Business Media Deutschland GmbH, 2021) Onur Orhan; Doğukan Başgöl; Muharrem Eren Tekin; Ahmet Gülseven; Mahmut Ali Gökçe; Evren Demir; Cansu Yurtseven; Orhan, Onur; Tekin, Muharrem Eren; Gökçe, Mahmut Ali; Demir, Evren; Yurtseven, Cansu; Gülseven, Ahmet; Başgöl, Doğukan; N.M. Durakbasa , M.G. Gençyılmaz
This study deals with multi-line balancing for multiple products. This problem originates from a real-life problem at a global heat boiler manufacturing company. The objective is to develop a solution method that enables create efficient line balances in a dynamic environment which maximizes the weighted average line efficiency and reduces waste of time for frequent line balancing procedures. Since weighted average efficiency is a key performance indicator for the company this paper focuses on the optimization of this measure. The proposed method is demonstrated with an implementation at three assembly lines where great majority of the company’s production takes place. For this problem an algorithm has been developed that creates a set of feasible scenarios (a scenario pool) in which total demand of each model is divided between available lines under capacity restrictions. For every scenario in the pool a custom multi model assembly line balancing MIP is created automatically and run. From the results best (most efficient) assignment of models’ demand to lines and corresponding line balances are obtained. Furthermore a user-friendly dynamic decision support system (DSS) is developed and proposed solution approaches are embedded in this DSS for the daily operations of the company. The developed DSS enables users to do an efficient line balancing in short computational time and provides the results with detailed line balancing reports. As this problem can be faced in various areas the proposed solution approaches can also be applied to different sectors and factories with little modification. © 2020 Elsevier B.V. All rights reserved.
Multi Objective Optimization for Intelligent Scheduling and Routing of Automated Guided Vehicle (AGV) Assisted Order Picking
(SPRINGER INTERNATIONAL PUBLISHING AG, 2024) Simge Guclukol Ergin; Mahmut Ali Gokce; Gökçe, Mahmut Ali; Ergin, Simge Güçlükol; C Kahraman; SC Onar; S Cebi; B Oztaysi; AC Tolga; IU Sari
This study addresses the complexities of efficient warehouse management and order picking crucial for modern supply chain success. It focuses on the implementation of Automated Guided Vehicles (AGVs) to enhance order picking processes involving selecting and retrieving items to fulfill customer orders. Challenges such as suboptimal picking strategies poor layout and lack of realtime visibility leads to inefficiencies. The research introduces a multi-objective mathematical model and a novel clustering algorithm aimed at optimizing AGV-assisted order picking by balancing the minimization of travel distance and AGV energy consumption against the investment cost of purchasing new AGVs. The model seeks to efficiently assign orders to AGVs and determine optimal routing to reduce total travel distance addressing the trade-off between operational efficiency and investment costs. The results obtained from executing the experimental design demonstrate that the proposed algorithm can solve most instances more quickly while the mathematical model is particularly effective in reducing travel distances.
Citation - WoS: 13
Citation - Scopus: 16
Multi-Period Vehicle Routing & Replenishment Problem of Neighbourhood Disaster Stations for Pre-Disaster Humanitarian Relief Logistics
(ELSEVIER, 2019) Mahmut Ali Gokce; Elif Ercan; Gökçe, Mahmut Ali; Ercan, Elif
Natural disasters are uncontrollable situations that affect human life directly. Despite the researches and technological progress it is still not possible to predict when or where the natural disaster will occur beforehand. Natural disasters cause severe loss of lives and damages. In addition they cause physical financial social and environmental losses. Pre-disaster during disaster and post-disaster activities are significant in order to decrease the losses caused by natural disasters. This study is about one of the pre-disaster activities. In the pre-disaster management process a new activity is being tried in Turkey. Called Neighborhood Disaster Stations containers filled with emergency relief items such as medicines painkillers antiseptics and canned goods are located at the different predetermined locations. It is important to keep items in these stations usable at all times. Since these commodities have expiration dates they need to be replenished periodically in order to remain useable at any time. The proper time for the replenishment should be determined by considering the probability of reselling or re-using the commodities with the maximum return as much as possible. However replenishing frequently will result in large operational costs. Therefore there is a trade-off between routing costs and replenishment. We propose a novel mixed integer-programming model in order to solve this problem. The proposed model determines the replenishment policy for each commodity in the containers and generates the route of each vehicle within a given planning horizon. The objective of this study is to maximize the total profit which is the difference between expected revenue from reselling and the transportation cost for total routing costs for time periods in the planning horizon. The model determines the replenishment date of each commodity in each disaster container and provides optimal route for each vehicle within planning horizon. The proposed mixed integer programming model is solved optimally for a small instance in IBM ILOG CPLEX Optimization Studio 12.8 and validation of the model is done. (C) 2019 IFAC (International Federation of Automatic Control) Hosting by Elsevier Ltd. All rights reserved.
Peak Period Inventory Planning for Apparel Industry
(Springer Science and Business Media Deutschland GmbH, 2024) Mahmut Ali Gökçe; Russell E. King; King, Russell; Gökçe, Mahmut Ali; N.M. Durakbasa , M.G. Gençyılmaz
The purpose of this study is the development of a mathematical/computer model for inventory planning for items with very sharp peaks in demand. The demand at peak periods for these items constitutes the most of the annual demand. The correct amount of inventory must be built before the peak due to maximum order quantity lead-time and maximum inventory level constraints. This target inventory is dependent on inventory carrying charges stockout costs and sales revenues. We suggest an alternative way of determining the shortage cost. The problem is modeled as a dynamic programming problem utilizing the value iteration method of Howard. We assume that the seasonality and the expected demands are known. The proposed model can be used to find the optimal ordering amounts to maximize the expected profit from the season depending on the number of weeks left until the end of season and the initial inventory on-hand. Multiple regression models are developed to predict the season performance based upon critical input factors. Results show that lead-time is the most important factor in determining the season performance. Also some characteristics of optimal ordering patterns are presented. © 2024 Elsevier B.V. All rights reserved.
Citation - Scopus: 1
Periodic Route Optimization for FMCG Distributors
(Springer Science and Business Media Deutschland GmbH, 2020) Onur Çopur; Mert Yildiz; Simru Göven; Ali Övünç Güneri; Alper Berke Yavuz; Mahmut Ali Gökçe; Cansu Yurtseven; Gökçe, Mahmut Ali; Yurtseven, Cansu; Çopur, Onur; Yavuz, Alper Berke; Güneri, Ali Övünç; Yıldız, Mert; Göven, Simru; M.N. Osman Zahid , R. Abd. Aziz , A.R. Yusoff , N. Mat Yahya , F. Abdul Aziz , M. Yazid Abu , N.M. Durakbasa , M.G. Gençyilmaz
Izmir based Information Technology (IT) solution provider develops supply chain management software tools for many customers from fast moving consumer goods sector (FMCG). Customers of the FMCG sector needs to be visited a certain number of times in a given period by sales representatives. The company must decide which customers must be visited in which sequence by each sales representative while obeying visit frequency and time windows requirements. These decisions have significant impact on total cost. For this reason finding an optimal route for every sales representative for each day of the planning horizon is important. This practically challenging and technically important problem can be described as periodic multiple depot traveling salesman problem with time windows (PMDTSPTW). We propose a novel mathematical model for the optimal solution of this problem. The proposed model minimizes the total distance traveled by sales representatives by deciding which sales representative will visit which customer on which day while following the time windows to collect demand data. The proposed model is applicable to any company from FMCG sector. The solution approach in this study is implemented and tested with real life including coordinates and location data of customers and sales representatives from Turkey’s largest beer distributor. The proposed model is solved using IBM ILOG CPLEX Optimization Studio version 12.8. The results show significant improvement over the current situation. To ensure efficient usage of the proposed approach a user-friendly decision support system (DSS) is constructed and implemented. © 2022 Elsevier B.V. All rights reserved.
Üretim ortamındaki otomatik yönlendirilmeli araçların (AGVs) çizelgeleme ve rotalama problemi için yeni bir senaryo temelli gürbüz çözüm yöntemi
(2022) Akkaya, Selen Burçak; Gökçe, Mahmut Ali
Otomatik Yönlendirmeli Araçların (AGV'ler) malzeme taşıma amacıyla kullanımı giderek daha popüler hale gelmiştir. Hızlı ulaşım sağlamaları, görevlere hızlıca atanabilmeleri ve nakliye kapasitesini arttırmalarının yanı sıra üretkenlik, güvenlik, kaynakların kullanım verimini arttırarak ve maliyetleri azaltarak, sisteme esneklik kazandırmaktadırlar. Bu faydaların elde edilebilmesi için AGV'lerin işlere sistematik bir şekilde atanması ve AGV'lerin üretim planlarını karşılayacak şekilde rotalanması ve çizelgelenmesi gerekir. Bu tez, bir atölye üretim ortamında istasyonlar arası taşıma işlerini sağlamak amacıyla kullanılan, kullanım amacına, taşıma ve pil şarj kapasitesine göre farklı tiplerden oluşan heterojen bir AGV filosunun çizelgeleme ve rotalama problemini incelemektedir. Amaç, siparişlere ait taşıma işlerinin geç teslimine atanan ceza maliyetini ve araçların enerji tüketimini en aza indireren gürbüz bir atama ve AGV'lere ait gürbüz rotaları ve çizelgeleri bulmaktır. Bunun amaçla bu tez, heterojen bir AGV filosu için bu kararların yanı sıra şarj planı ve enerji tüketimini de gözeten, senaryo tabanlı yeni bir gürbüz karma tamsayılı doğrusal programlama modeli önerilerek literatüre katkıda bulunmaktadır. Önerilen model öncelikle, IBM OPL CPLEX kullanılarak bir test senaryosu ile doğrulanmıştır. Yapılan deney tasarımı ile önerilen modelin performansı ve belirli parametrelerin model üzerindeki etkisi değerlendirilmiştir.
Warehouse Design and Order Picking Algorithms for Apparel Industry
(Springer Science and Business Media Deutschland GmbH, 2024) Deniz Su Güntekin; Egemen Şahin; Elif Ünlü; Nesrin Özbay; Mahmut Ali Gökçe; Simge Güçlükol Ergin; Güntekin, Deniz Su; Gökçe, Mahmut Ali; Şahin, Egemen; Ünlü, Elif; Özbay, Nesrin; Ergin, Simge Güçlükol; N.M. Durakbasa , M.G. Gençyılmaz
Warehouse management has a critical role for success for the apparel industry. It is important because it ensures effective inventory control efficient order fulfillment optimal space utilization labor efficiency cost reduction and customer satisfaction which all directly effects the bottom line. A particularly important part of this optimization includes the design of the warehouse. In this study various product placement and order-picking scenarios have been studied in combination with numerous warehouse designs and implementation is presented for a large apparel company. The implementation was done in the warehouse of one of the largest Retail Textile Company specializing in women’s apparel production. First a comprehensive literature review was conducted for this study. As a result of the literature review different picking and routing algorithms were combined. The solution was developed first by building a simulation model. Different placement scenarios scenarios for assigning orders to workers and routing algorithms are presented in conjunction with warehouse designs. The aim is to reduce the total product placement and picking times and increase the efficiency of workers by utilizing different placement and picking algorithms. With this study the total placement and picking time is reduced by 36.56% compared to the current system. © 2024 Elsevier B.V. All rights reserved.