Showing 18 results for Logistics
E. Teimoury, I.g. Khondabi , M. Fathi ,
Volume 22, Issue 3 (9-2011)
Abstract
Discrete facility location, Distribution center, Logistics, Inventory policy, Queueing theory, Markov processes, |
The distribution center location problem is a crucial question for logistics decision makers. The optimization of these decisions needs careful attention to the fixed facility costs, inventory costs, transportation costs and customer responsiveness. In this paper we study the location selection of a distribution center which satisfies demands with a M/M/1 finite queueing system plus balking and reneging. The distribution center uses one for one inventory policy, where each arrival demand orders a unit of product to the distribution center and the distribution center refers this demand to its supplier. The matrix geometric method is applied to model the queueing system in order to obtain the steady-state probabilities and evaluate some performance measures. A cost model is developed to determine the best location for the distribution center and its optimal storage capacity and a numerical example is presented to determine the computability of the results derived in this study .
, , ,
Volume 23, Issue 2 (6-2012)
Abstract
Design of a logistics network in proper way provides a proper platform for efficient and effective supply chain management. This paper studies a multi-period, multi echelon and multi-product integrated forward-reverse logistics network under uncertainty. First, an efficient complex mixed-integer linear programming (MILP) model by considering some real-world assumptions is developed for the integrated logistics network design to avoid the sub-optimality caused by the separate design of the forward and reverse networks. Then, the stochastic counterpart of the proposed MILP model is used to measure the conditional value at risk (CVaR) criterion, as a risk measure, that can control the risk level of the proposed model. The computational results show the power of the proposed stochastic model with CVaR criteria in handling data uncertainty and controlling risk levels.
Romina Madani, Amin Ramezani, Mohammad Taghi Madani Beheshti,
Volume 25, Issue 4 (10-2014)
Abstract
Today, companies need to make use of appropriate patterns such as supply chain management system to gain and preserve a position in competitive world-wide market. Supply chain is a large scaled network consists of suppliers, manufacturers, warehouses, retailers and final customers which are in coordination with each other in order to transform products from raw materials into finished goods with optimal placement of inventory within the supply chain and minimizing operating costs in the face of demand fluctuations. Logistics is the management of the flow of goods between the point of origin and the point of consumption. One issue in Logistics management is the presence of possible long delays in goods transportation. In order to handle long delays, there are two possible solutions proposed in this paper. One solution is to use Model Predictive Controllers (MPCs) using orthonormal functions (Laguerre functions) and the other is to change supply chain model in which an integrator is imbedded. To this end, the two mentioned solutions will be implemented on a supply chain with long logistics delays and the results will be compared to classical MPC without using orthonormal basis and augmented model for different type of customer demand (constant, pulse and random demand).
Ebrahim Teimoury, Farshad Saeedi, Ahmad Makui,
Volume 28, Issue 1 (3-2017)
Abstract
Recently, urbanization has been expanded rapidly in the world and a number of metropolitan areas have been appeared with a population of more than 10 million people. Because of dense population in metropolitan and consequently increasing the delivery of goods and services, there has been a lot of problems including traffic congestion, air pollution, accidents and high energy consumption. This made some complexities in distribution of urban goods; Therefore, it is essential to provide creative solutions to overcome these complexities. City logistics models can be effective in solving these complexities.
In this paper, concepts and definitions related to city logistics are explained to provide a mathematical model in order to design city logistics distribution network aim at minimizing response times. This objective is effective for goods and emergency services, especially in times of crisis and also for goods that are delivered as soon as possible. This is a three-level network and has been used in modeling of queuing theory. To validate the model, a numerical example has been established and results of the model have been explained using BARON solver in Gams software. Finally, conclusions and recommendations for future research are presented.
Lucas Sequeira, Daniel Rossit,
Volume 32, Issue 2 (6-2021)
Abstract
The logistical problems that companies must face tend to have conflicting interests between customers and service providers, which makes them difficult to solve. In turn, when the activities involve the transport of hazardous materials, the problem becomes critical in security terms, and makes logistics operations even more difficult. In the hazardous materials transportation literature, problems related to the routing of vehicles and the geographic location of supply or service centres are often addressed. However, there are not many studies related to the study of the loading, unloading and weighing operations of trucks that handle hazardous materials within industrial plants. That is why this work presents a case study of the installation of a new truck balance in an industrial plant in Argentina. To do this, the internal logistics operation and the current state of the plant's infrastructure are analyzed. A detailed study of the alternatives for the location of the balance was carried out following the criteria set by the company's management and the problem was solved using an empirical weighting method coordinated with the heads of the Supply Chain Department. A satisfactory solution was obtained.
Gholamreza Moini, Ebrahim Teimoury, Seyed Mohammad Seyedhosseini, Reza Radfar, Mahmood Alborzi,
Volume 32, Issue 4 (12-2021)
Abstract
Productions of the industries around the world depend on using equipment and machines. Therefore, it is vital to support the supply of equipment and spare parts for maintenance operations, especially in strategic industries that separate optimization of inventory management, supplier selection, network design, and planning decisions may lead to sub-optimal solutions. The integration of forward and reverse spare part logistics network can help optimize total costs. In this paper, a mathematical model is presented for designing and planning an integrated forward-reverse repairable spare parts supply chain to make optimal decisions. The model considers the uncertainty in demand during the lead-time and the optimal assignment of repairable equipment to inspection, disassembly, and repair centers. A METRIC (Multi-Echelon Technique for recoverable Item Control) model is integrated into the forward-reverse supply chain to handle inventory management. A case study of National Iranian Oil Company (NIOC) is presented to validate the model. The non-linear constraints are linearized by using a linearization technique; then the model is solved by an iterative procedure in GAMS. A prominent outcome of the analyses shows that the same policies for repair and purchase of all the equipment and spare parts do not result in optimal solutions. Also, considering supply, repair, and inventory management decisions of spare parts simultaneously helps decision-makers enhance the supply chain's performance by applying a well-balanced repairing and purchasing policy.
Qurtubi Qurtubi, Muhammad Suyanto, Anas Hidayat, Elisa Kusrini,
Volume 34, Issue 3 (9-2023)
Abstract
Various of studies on firm’s performance have been performed by reserachers involving many variables as antecedents, logistics performance is one of them. Aside from significantly supporting the firm, it also identifies firm’s performance as standard to keep up in short and long-term competition. There are several types of criteria in logistics performance, however they are all only classified in three dimensions which are efficiency, effectiveness and differentiation. From the literature review, it was suggested that halal certification could affect logistics performance. This article proposes research model that integrates logistics efficiency, logistics effectiveness, logistics differentiation and halal certification as the dimensions of logistics performance. . It is expected to provide theoretical contribution by explaining causal relationship among variables and provide intact knowledge by considering the firm’s performance that is determined by dimensions of logistics performance. Literature review is applied for this research. Based on the result and discussion, it can be concluded that halal certification potentially could become a new dimension for logistics performance in addition to other existing three dimensions, yet it takes empirical research support strengthen this proposed model.
Tesfaye K. Torban, Mathewos Ensarmu, Chala Dechassa,
Volume 34, Issue 3 (9-2023)
Abstract
Environmental sustainability is a growing concern for businesses and organizations due to climate change trends. This study aims to examine the direct impact of institutional pressures, green procurement (GP), and reverse logistics (RL) on environmental performance (EVP). The mediating influences of RL and GP on institutional pressure and EVP are also examined. The study uses a quantitative method where data is gathered from the CEO, operations, human resources, logistics, and procurement managers of 165 industrial park firms using customized questionnaires. The data is analyzed using the PLS-SEM software (SmartPLS 4). The results suggest that the adoption of institutional pressures has a significant effect on GP and RL, and the findings show that GP does not improve EVP. However, the implementation of RL mediates the relationship between institutional pressure and EVP. The study develops a comprehensive empirical model that tests the joint influence of institutional pressure- GP-RL-EVP model was developed and validated. The findings indicate that institutional pressure and RL help firms advance EVP.
Nur Iftitah, Qurtubi Qurtubi, Muchamad Sugarindra,
Volume 34, Issue 4 (12-2023)
Abstract
This research aims to determine the scope and pattern of research and understand trends in class-based storage research, to deliver the latest research on the topic of class-based storage for future studies. This study is based on data derived from several journal publications, limited only to publication years of 2012 to 2023. Harzing's Publish or Perish and VOSviewer software were used in data collection. Therefore, 980 articles were obtained based on keywords and processed by using bibliometric analysis. From the results of bibliometric research on the topic of class-based storage, identification of trends and patterns on research growth is obtained, analyzing renewal, obsolescence, and distribution of references, estimating productivity, author, year of publication, most-contributed publishers, and collaboration among authors who discussing interrelated topics. This research shows that in bibliometric studies in class-based storage literature, by involving analysis through keywords contained in titles and abstracts, as well as various analyses of years of publication, most publications are able to deepen and expand the literature in the previous class-based storage-related research. So that the findings in terms of assessment techniques and relationships can be used as information for future researchers in such fields of study. Research on bibliometrics is the main reference, especially in the arrangement of facility layout and warehouse management. The originality provided by this study lies in the presentation of differences and similarities between current researchers and previous researchers and the processing of publication databases based on class-based storage journals. So that all published information on the topic of class-based storage in the last 10 years (2012-2023) could become a basis and reference for further research.
Dian Dewi, Yustinus Hermanto, Martinus Sianto, Jaka Mulyana, Dian Trihastuti, Ivan Gunawan,
Volume 35, Issue 2 (6-2024)
Abstract
Supply chain agility (SCA) has emerged as a significant focus for industries and businesses, serving as a cornerstone for gaining a competitive edge and playing a pivotal role in supply chain management. This importance is further underscored in the context of Product–Service Systems (PSS), which involve the development of both products and services. Despite the existing body of research on SCA and PSS, there has been a notable dearth of empirical studies examining the readiness of PSS SCA. This study makes a substantial contribution by developing a valid and reliable framework to assess the readiness of PSS for supply chain agility. The process involves defining domains, generating items, analyzing agreement among raters, testing for response bias, and conducting exploratory and confirmatory factor analyses. Using structural equation modeling, the model's validity and reliability were evaluated through an online survey with 405 participants from official motorcycle service partners. The findings identify six key capability constructs: collaboration, knowledge transfer, service partner development, information sharing, logistic integration and supply chain agility. This examination of PSS SCA readiness and its constructs provides a validated tool for industry practitioners to enhance their supply chain agility.
Melinska Ayu Febrianti, Qurtubi Qurtubi, Roaida Yanti, Hari Purnomo,
Volume 35, Issue 2 (6-2024)
Abstract
The retail industry is a vital sector of the world economy and is characterized by fierce competition, tight profit margins, and demanding consumers. Understanding customer buying behavior patterns is essential in devising the best retail strategy to enhance product sales. This research aims to comprehend customer shopping behaviors based on retail sales transactions and formulate the best strategies. By employing multi-level association rules, the dataset is arranged hierarchically into categories, sub-categories, and items. The sales transaction data used comprises 5830 transaction records over a month. The results of this study reveal 24 associations of categories, 49 associations of sub-categories, and 12 associations of product items. Moreover, the proposed marketing strategy offers recommendations including store layout improvement, planogram design, and bundled product offerings. This research addresses the gap in empirical evidence from a previous study and suggests further observation from diverse locations to authenticate the findings, which may yield various outcomes
Mary Jiny D, G Navamani, Raman Kumar, Željko Stević, Darjan Karabašević, Rajender Kumar,
Volume 35, Issue 3 (9-2024)
Abstract
The increasing demand for food delivery services driven by technological innovations has led to a surge in online shopping and food ordering. Efficient logistics play a crucial role in connecting customers with restaurants seamlessly. In this context, the practical application of graphical networks is explored in this article to streamline food delivery operations. We introduce a novel parameter eternal m-certified domination number denoted by γmcer∞(G) , which represents the minimum number of guards needed to handle any sequence of single orders using multiple-guard movements, ensures that the guard arrangement consistently constitutes a certified dominating set. A case study is presented, illustrating how this concept can be employed to de-crease human resources in a food delivery start-up. This research contributes to optimizing food delivery logistics and reducing operational costs, thereby enhancing the efficiency of the food delivery industry.
Rahma Fariza, Melinska Ayu Febrianti, Qurtubi Qurtubi, Hari Purnomo,
Volume 35, Issue 4 (12-2024)
Abstract
A business faces challenges in terms of product structuring, design, and space layout; it needs to adapt traditional design management models to scientific developments, like customer shopping behavior data. This article contains a systematic review of planograms and is essential because a similar complete literature review has yet to be found. Therefore, this research is necessary, especially for business actors such as retailers and suppliers. This research aims to analyze studies on shelf-space allocation and store layout and provide advice for future research. This study used the systematic review methodology to incorporate relevant literature, of which 50 articles were later obtained. The review protocol guides a comprehensive and systematic analysis of the articles. This study proposes potential avenues for future research to offer a thorough and precise examination of the impact of shelf-space allocation and store layout. The gaps in previous studies are opportunities to create more complex and comprehensive research results on similar topics. This article added scientific value by presenting an exhaustive literature review, and it can fill the theoretical gap by completing the previous literature review.
Martin D Arango-Serna, Cristian G Gomez-Marin, Conrado Augusto Serna-Uran, Silvana Ruiz-Moreno,
Volume 36, Issue 1 (3-2025)
Abstract
In recent years changes in freight transport demand, both locally and internationally, have significantly increased cargo flows to and from logistics centers. As a result, it is essential to develop effective methods for assessing freight accessibility to road corridors designated for land cargo transportation. This paper proposes a methodology that facilitates the freight accessibility analysis to a road corridor for land cargo transportation. The accessibility analysis considers several key variables such as the mobilized tons, the overall conditions of the roads, the route lengths connected to the corridor, and origin-destination nodes associated with the productive chains mobilized by this transportation mode. We validate the methodology through a comprehensive case study conducted in Colombia. The results reveal road corridors such as Llanos de Cuivá (Yarumal) - La Apartada (Córdoba), and Soledad - Barranquilla present the lowest accessibility measure and require infrastructure investments to enhance road corridor accessibility and promote the efficient transportation of goods. Furthermore, it offers valuable insights into characterizing areas with significant cargo generation and reception, enabling targeted improvements in transportation industry responsiveness.
Mohamed Hadi Al Najdawi, Zainab Al Ghurabli, Raghda Raafat, Ahmad Aburayya,
Volume 36, Issue 3 (9-2025)
Abstract
This study investigates regulatory gaps impeding artificial intelligence (AI) integration in public sector logistics, revealing how fragmented legislative frameworks hinder operational efficiency and innovation. Through a quantitative cross-sectional survey of 182 legal professionals, public employees, and AI/legal scholars using stratified purposive sampling and validated instruments (Cronbach’s α=0.985) we identified statistically significant stakeholder divergences (*p*<0.05) via χ² tests and Cramer’s V effect sizes. Key findings demonstrate that: (1) legal experts prioritize regulatory clarity deficits (M=4.62), while public staff emphasize institutional resistance (M=4.41); (2) human capital training is systematically undervalued (M=2.57, V=0.26) despite its theoretical importance; and (3) while regulation enhances operational efficiency (M=4.36), it paradoxically inhibits logistical innovation (M=2.48), exposing a critical innovation-governance disconnect. The study’s core contribution, a Dynamic Institutional Alignment Framework, resolves this tension through three pillars: human-centered regulatory design integrating legal-technical dimensions, adaptive policy sandboxes synchronized with AI advancement cycles, and stakeholder-specific implementation pathways. By embedding institutional adaptability within global compliance standards (EU AI Act, OECD Principles), this framework advances AI governance theory and offers public institutions actionable strategies for balancing technological advancement with accountability.
Aizi Mouna, Bouyaya Linda, Bouguern Siham,
Volume 37, Issue 1 (3-2026)
Abstract
This study applies a Genetic Algorithm (GA) to optimize the Vehicle Routing Problem with Time Windows (VRPTW) for NAFTAL, Algeria’s national fuel distribution company. The model minimizes both fleet size and total travel distance while achieving high compliance (99.3%) with customer time constraints. Using operational data from the Constantine regional network one depot serving 148 service stations (149 nodes in total ), the GA achieved optimal solutions deploying 94 vehicles covering 15,415.63 km. Results demonstrated exceptional convergence stability (σ = 0.00 across 40 runs) and high computational efficiency (under 60 seconds per optimization run). Sensitivity analyses confirmed the robustness of the calibrated configuration, highlighting its reliability and scalability for real-world logistics. The proposed framework provides NAFTAL with a cost-effective, consistent, and practical decision-support tool for optimizing fuel-delivery operations. Future research will focus on integrating machine learning for demand prediction, extending the model to multi-product and heterogeneous-fleet routing, and enabling adaptive real-time optimization to support smart and sustainable logistics.
Shereen Abdelaziz, Munjiati Munawaroh,
Volume 37, Issue 1 (3-2026)
Abstract
This study conducts a comprehensive bibliometric analysis to examine the intersection of sustainable logistics and supply chain resilience, aiming to uncover emerging trends, influential factors, and critical gaps in the literature. Using the Scopus database, 480 publications published between 2009 and 2024 were systematically analyzed through VOSviewer and Biblioshiny. The findings highlight six dominant themes—decarbonization, reverse logistics, optimization models, circular economy practices, digital transformation, and risk mitigation—that collectively position sustainability as a driver of resilience. The analysis focuses on sustainable logistics practices, including green logistics, circular economy principles, and reverse logistics, alongside digital transformation technologies such as IoT, blockchain, and predictive analytics, to assess their integration into resilience strategies. The analysis reveals a fragmented approach to integrating sustainability and resilience, with practices often treated in isolation. Results indicate that sustainable logistics practices enhance resource efficiency and adaptability but are constrained by the lack of holistic frameworks that integrate diverse sustainability practices with resilience strategies. While environmental dimensions and digital technologies are recognized as critical enablers, social and governance dimensions remain underexplored. Adoption disparities further hinder progress, particularly among SMEs, resource-constrained sectors, and underrepresented regions like Africa and South Asia. The study highlights opportunities to advance foundational theories, including Circular Economy Theory, Dynamic Capabilities Theory, and the LARG model, for aligning sustainability and resilience objectives. The study highlights the importance of developing unified, data-driven frameworks that incorporate ESG principles, sector-specific applications, and inclusive approaches to address geographic and financial disparities. Practically, integrating digital technologies with sustainable logistics practices can strengthen transparency, efficiency, and agility. Meanwhile, policy interventions, targeted incentives, and multi-stakeholder collaboration are essential to overcome implementation barriers and achieve operational sustainability and resilience integration.
Samaneh Valipour Khonakdari, Hadi Nasseri, Zohreh Akbari,
Volume 37, Issue 2 (6-2026)
Abstract
This study develops a comprehensive circular economy–based reverse logistics network for apple by explicitly integrating agility and resilience considerations under mixed uncertainty. The proposed network encompasses multiple echelons, including farms, collection centers, recycling centers, animal husbandry units, and energy and compost demand points, enabling effective waste recovery and value creation. A multi-objective mathematical programming model is formulated to simultaneously maximize economic performance, minimize node criticality as a proxy for resilience, and enhance service levels as an indicator of agility. To address the inherent uncertainty in parameters, a robust stochastic–possibilistic optimization framework is employed. Furthermore, the model is solved using a recently developed method named the Fuzzy Multi-Choice Chebyshev Goal Programming with Utility Function (FMCCGP-UF) method. The practical relevance of the proposed approach is validated through its application to a real-world case study of the apple reverse supply chain in Iran. Results reveal that increasing processing and collection capacities improve economic outcomes while simultaneously strengthening agility and resilience. The network design leads to the establishment of recycling centers #2 and #5, as well as collection centers #1, #3, and #4. Critical nodes are identified as recycling center #2 (periods 2 and 5) and collection center #1 (periods 3 and 5) and collection center #2 (periods 1 and 5). The service levels achieved are 0.73 for animal husbandry units, 0.78 for compost demand points, and 0.69 for energy demand points. Furthermore, increasing processing and collection capacities improves economic outcomes while simultaneously strengthening agility and resilience. A higher proportion of recyclable products substantially enhances value recovery and service levels, albeit with implications for node criticality.
