Transshipment Problem Research Articles

Application and performance evaluation of assigning shortest mini-max method on trans-shipment problem with flow restriction over some path

Application and performance evaluation of assigning shortest mini-max method on trans-shipment problem with flow restriction over some path

Vosviewer-Based Bibliometric Review of Transshipment Location Problem From 2000 to 2023

Objective: This study conducts a comprehensive bibliometric review of the Transshipment Location Problem (TLP) by identifying key authors, countries, journals, and research areas. It also maps the evolution of TLP and explores methodologies and tools used for optimizing logistical and distribution systems. Theoretical Framework: TLP, a variant of the classical transshipment problem, has gained attention for its role in optimizing supply chain networks. It involves both proactive transshipment (planned inventory management) and reactive transshipment (responding to unexpected events or shortages). Method: This study applies a bibliometric analysis methodology using VOSviewer to analyze publications extracted from the Scopus database. The analysis focuses on key bibliometric indicators such as co-authorship, co-citation, and keyword co-occurrence. The dataset comprises 432 selected articles published between 2000 and 2023. Results and Discussion: The review reveals that optimization tools, particularly in transportation and inventory management, are widely applied in TLP studies The United States, China, and Germany are leading contributors to TLP research. Lateral transshipment strategies are increasingly employed to enhance supply chain flexibility. A small group of influential researchers drives the field through collaborations and citations. Research Implications: The review provides valuable insights for future research, highlighting gaps in applying optimization methods in emerging fields like healthcare. It offers a clear view of the geographical and institutional landscape of TLP research and suggests areas for future study, such as sustainability. Originality/Value: This review fills a gap in the literature by systematically mapping TLP research’s evolution and its growing relevance in logistical systems optimization across various industries.

A Study of the Main Mathematical Models Used in Mobility, Storage, Pickup and Delivery in Urban Logistics: A Systematic Review

This systematic review investigates the main mathematical models applied in urban logistics, focusing on routing, location and transshipment problems. The study addresses the growing demand for efficient and sustainable logistics solutions driven by population growth and the expansion of e-commerce. A thorough analysis of 57 scientific articles was carried out, covering deterministic and stochastic methodologies, as well as heuristic and exact solutions. This review revealed that heuristic methods are predominant due to their computational efficiency. Combining exact methods with heuristics has proven effective for complex logistics scenarios, increasing accuracy and efficiency. Synchronization and intermediate stops have also emerged as critical factors in optimizing logistics operations. This review highlights the diversity of methodologies and the need for sustainable and efficient models. The integration of stochastic simulations remains limited, representing a research gap where stochastic models have been shown to provide more robust solutions in addressing the uncertainties inherent in logistics operations. This integration can increase the robustness and applicability of logistics solutions in urban environments. By highlighting the strengths and limitations of current approaches, it paves the way for future research to develop more robust and adaptable solutions to urban logistics challenges, emphasizing interdisciplinary collaboration and the use of real-world data.

A technique to solve Transshipment Problem with Asymmetric Pentagonal Fuzzy Numbers

In order to draw comparison in largely used fuzzy numbers, ranking of fuzzy numbers becomes important. In this paper, a new method for ranking Asymmetric Pentagonal Fuzzy Numbers (APFN) is proposed. In this method, the pentagonal fuzzy numbers are scored by obtaining their centers of gravity using left and right areas associated with them. Further, we propose a direct technique for solving fuzzy Transshipment Problem (TsP) in which costs are represented as Asymmetric Pentagonal Fuzzy Numbers. The solution so obtained is fuzzy optimal solution. The validity of proposed methodology is illustrated through numerical examples.

A Modified Emperor Penguin Optimizer Algorithm for Solving Fixed-Charged Transshipment Problem

A Modified Emperor Penguin Optimizer Algorithm for Solving Fixed-Charged Transshipment Problem

A multiobjective mathematical model for a humanitarian logistics multimodal transportation problem

PurposeThe purpose of this paper is to introduce a three-echelon multimodal transportation problem applied to a humanitarian logistic case study that occurred in Mexico.Design/methodology/approachThis study develops a methodology combining a transshipment problem and an adaptation of the multidepot heterogeneous fleet vehicle routing problem to construct a mathematical model that incorporates the use of land-based vehicles and drones. The model was applied to the case study of the Earthquake on September 19, 2017, in Mexico, using the Gurobi optimization solver.FindingsThe results ratified the relevance of the study, showing an inverse relationship between transportation costs and delivery time; on the flip side, the model performed in a shorter CPU time with medium and small instances than with large instances.Research limitations/implicationsWhile the size of the instances limits the use of the model for big-scale problems, this approach manages to provide a good representation of a transportation network during a natural disaster using drones in the last-mile deliveries.Originality/valueThe present study contributes to a model that combines a vehicle routing problem with transshipment, multiple depots and a heterogeneous fleet including land-based vehicles and drones. There are multiple models present in the literature for these types of problems that incorporate the use of these transportation modes; however, to the best of the authors’ knowledge, there are still no proposals similar to this study.

Solution of a transshipment problem with uncertain parameters under impaired and enhanced flow

Solution of a transshipment problem with uncertain parameters under impaired and enhanced flow

Robust transshipment problem under consistent flow constraints

AbstractIn this article, we study robust transshipment under consistent flow constraints. We consider demand uncertainty represented by a finite set of scenarios and characterize a subset of arcs as so‐called fixed arcs. In each scenario, we require an integral flow that satisfies the respective flow balance constraints. In addition, on each fixed arc, we require equal flow for all scenarios. The objective is to minimize the maximum cost occurring among all scenarios. We show that the problem is strongly ‐complete on acyclic digraphs by a reduction from the ‐Sat problem. Furthermore, we prove that the problem is weakly ‐complete on series‐parallel digraphs by a reduction from a special case of the Partition problem. If in addition the number of scenarios is constant, we observe the pseudo‐polynomial‐time solvability of the problem. We provide poly‐nomial‐time algorithms for three special cases on series‐parallel digraphs. Finally, we present a polynomial‐time algorithm for pearl digraphs.

Clustering retail stores for inventory transshipment

Rapid growth in the world of e-commerce is forcing traditional retailers to rethink their operational efficiency and revenue/cost streams. Retailers are facing increasing pressure to better utilize in-store inventory and reduce end-of-season markdowns. Transshipments between stores can re-balance inventory levels while preventing shortages and backorders. However, the joint inventory and transshipment problem is difficult to optimize in an extensive network, and many retailers lack the capital and managerial bandwidth required to create a system capable of transshipments between any two stores in a network of hundreds. We consider two multi-location newsvendor problems with reactive and proactive transshipments, respectively. We propose clustering stores into transshipment groups while considering both demand correlation and physical distance between locations. Since minimizing demand correlation does not follow the triangle inequality, we introduce two modified clustering algorithms that outperform existing algorithms for distance- and correlation-based clustering. For a given set of clusters, we mathematically model these two problems considering total system profit. In addition, we quantify the performance of distance-based and correlation-based clustering under several inventory ordering and transshipment policies to show the robustness of our results. To verify our methods, we test the proposed methodology using grocery sales data from IRi over three years in Houston and Dallas, TX and liquor licensee purchase information over three years from the Iowa state government. We present correlation, transshipment, and profitability analysis. We show that when demand correlation is present and stable over time, clustering based on demand correlation can maintain high transshipments and profits while decreasing solution complexity.

A note on the quickest minimum cost transshipment problem

Klinz and Woeginger (1995) prove that the minimum cost quickest flow problem is NP-hard. On the other hand, the quickest minimum cost flow problem can be solved efficiently via a straightforward reduction to the quickest flow problem without costs. More generally, we show how the quickest minimum cost transshipment problem can be reduced to the efficiently solvable quickest transshipment problem, thus adding another mosaic tile to the rich complexity landscape of flows over time.

The Influence of the Corona-Virus on the Tunisian Supply Chain and Transshipment Problem

This article aims to provide results of the impact of the Corona-Virus pandemic on the functioning of Tunisian companies. Based on a sample of these companies, the results showed a strong disruption of the various links in the supply chain following the generalized confinement of the population and the closure of borders.Overall, this study contributes both to the study of the effect of Corona-Virus on Supply Chain management and to the implications of the literature in this field and has important practical implications.We therefore sought to find out which links in the supply chain were the most impacted by applying ARENA modeling.The findings suggest that the analysis of the results makes it possible to detect the manifest existence of specific operating models.The Lateral-Transshipment and Commodity Allocation problem in the context of the COVID-19 outbreak has many novel features. For this, we propose a new multi-objective optimization model for Lateral-Transshipment of emergent products in two steps. The objectives envisaged are the optimization of the quality of the transhipped product, the satisfaction of customer demand and the minimization of the overall cost including the shortage penalty.

Quickest Transshipment in the Prioritized Evacuation Network

Flow maximization, time minimization, and cost minimization are three main aspects of mathematical optimization problems. The evacuation planning problems are about flow maximization and/or time minimization problems in different dynamic evacuation networks. The quickest transshipment problem in such a network is to send exactly the right amount of flow out of each source and into each sink in the minimum overall time. In evacuation planning problems, the term flow stands for either the evacuees or the evacuees carrying vehicles. Here, we use the quickest transshipment strategy in a prioritized evacuation network. It consists of a collection and an assignment sub-network as the primary and secondary sub-networks, respectively. Pick-up locations are prioritized in the collection network. By treating such pick-up locations as sources, the available set of transit buses is assigned in the assignment sub-network to shift the evacuees to the sinks to achieve the quickest transshipment. Such an evacuation planning strategy is better suited for the simultaneous collection, assignment, and evacuation process in the prioritized evacuation network.

Optimal replenishment and transshipment management with two locations

AbstractWe study the problem of optimally managing an inventory system with backorders over a finite time horizon where the objective is minimization of expected total discounted costs. The system consists of two locations each stocking the same product. At the beginning of each time period decisions are made about replenishment at each location and about any quantity to transship between the locations before demand is observed. Leveraging the L♮‐convexity of the problem's cost function; we characterize the optimal replenishment and transshipment policy for this system. More specifically, we show the optimal policy can be described using switching curves monotone in the system state. We also discuss two extensions. For a lost‐sales model, we establish L♮‐convexity and apply it to characterize the optimal policy, simplifying the analysis found in previous work. In the other extension, we investigate the optimal policy for a partial transshipment problem where only one location orders from the external supply source and then transships to the other location.

Optimising fully fuzzy interval integer transshipment problems

In this paper, we focus on solving fully fuzzy interval integer transshipment (FIIT) problems where the unit shipping costs, available supply capacities, and required destination demands are triangular fuzzy interval integers. An innovative method namely, back order sequence method has been developed for finding an optimal solution of the fully FIIT problem. The proposed method provides that the optimal values of decision variables and objective function value for the fully FIIT problem are fuzzy interval integers. A numerical example is presented to illustrate the solution procedure of optimising fully FIIT problems. The optimal solution to the transshipment problem by the proposed method can help the managers to take an appropriate decision regarding transshipments.

Solving Interval Integer Transshipment Problems with Rough Nature

Solving Interval Integer Transshipment Problems with Rough Nature

Stochastic Programming Model for Lateral Transshipment Considering Rentals and Returns

Supply chain management is a large scale planning under uncertainty. It is significant that building an efficient supply chain under uncertain condition; however, it is difficult. There are many traditional inventory transshipment models targeting only rental, not including return. This study provides the uncertainty between rentals and returns by scenarios with multi-period stochastic programming model of inventory transshipment problems. The moment matching method was used to reduce the amount of the scenarios, and the comparativeexperiment shows the utility of this study model.

Integrated Inventory Transshipment and Missing-Data Treatment Using Improved Imputation-Level Adjustment for Efficient Cross-Filling

This research investigates an integrated problem of transshipment for cross-filling and imputation for missing demand data. Transshipment for cross-filling has proved effective in mitigating shortages with relatively low inventory, thus reducing resource consumption in inventory management. Although accurate demand data are critical for cross-filling decision making, some demand data are inevitably incomplete. These missing data should be treated for effective transshipment operations. Despite the importance, these missing data issues have not been adequately studied for transshipment problems. This paper addresses how transshipment can be conducted under missing demand conditions. A novel integrated problem is established to combine demand-data imputation processes and transshipment decisions. Imputation strategies and new algorithms suitable for transshipment are developed to handle missing demand data. Diverse demand and transshipment cases are analyzed for cost-effectiveness. The analysis uncovers that conventional straightforward imputation methods result in inferior transshipment decisions. The study also reveals that imputed values should be adjusted to appropriate levels for transshipment to be effective. The strong interplay between imputation processes and shortage prevention is also discovered for transshipment with missing demand. This study demonstrates how inventory transshipment can be carried out successfully with appropriate treatment of missing demand data in practice.

Transshipment and Routing Model for Multi-Product Planning and Distribution at a Refreshment Company in Bogota, Colombia

In this article, a model is established for the planning of the weekly distribution of refreshments in a company that produces 6 types of beverages in 3 Production Centers, with the potential use of 3 Distribution Centers and supplying 22 Consumer Centers located in Bogota. Due to the impact of transportation costs on the company profits, it is necessary to determine the optimal planning of the allocation of sources to destinations in the nodal network of the system and its subsequent routing with two types of vehicles. Therefore, a two-phase model is proposed. In the first, the initial optimal assignments are established by comparing two techniques; one based on the Open Transshipment Problem (OTP) and the other on the Capacitated Transshipment Problem (CTP), which determine the trips to be made from production centers to consumer centers using distribution centers as intermediaries. This comparison allowed to analyze its efficiency to choose the model with the lowest cost and number of trips. In the second phase, routing was performed on routes that do not use the full capacity of the vehicles. The routes were established through the Travelling Salesman Problem (TSP). As a result, a comprehensive model was obtained to carry out the planning of the product distribution, obtaining in Phase II the use of the OTM model, which presented 14% less distance; 2.6% less time and 0.28% less than the total cost compared to the CTP model. In Phase II 5 routes were obtained, of which Distribution Center 2 covers 59% of customers.

DAMPAK KEBIJAKAN TRANSHIPMENT OLEH INDONESIA PADA INDSUTRI PRODUK OLAHAN IKAN THAILAND

The problem of transhipment is a matter of transitional transport or modified transportation issues. This transit place can receive supplies and can deliver goods. The main purpose of the transshipment problem is to minimize the cost of the distribution of goods delivered from the place of origin to the destination even though through the transit point. The problem in this research is with the policy of transhipment issued by Indonesian government causing negative impact to fishery industry, especially processed fishery product in Thailand country The eradication of fish theft in Indonesian waters had a direct impact on Thailand's fishery exports which affected the country's gross domestic product (GDP). Thailand National Economic and Social Development Board (NESDB) data reveal that the contribution of the fishery sector to Thailand's GDP has decreased drastically. The average contribution of the fishery sector to Thailand's GDP has been recorded at 1.6 percent, while in the third quarter of 2015 it contributed minus 3.1 percent. While the Ministry of Marine Affairs and Fisheries (KKP) noted in 2013 to second quarter 2014, Thai fishery industry has decreased.

An Enumeration Technique for Transshipment Problem in Neutrosophic Environment

An Enumeration Technique for Transshipment Problem in Neutrosophic Environment