Modeling and solving a five-echelon location–inventory–routing problem for red meat supply chain

Kybernetes ◽  
2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Misagh Rahbari ◽  
Seyed Hossein Razavi Hajiagha ◽  
Mahdi Raeei Dehaghi ◽  
Mahmoud Moallem ◽  
Farshid Riahi Dorcheh
Keyword(s):  
Supply Chain ◽  
Red Meat ◽  
Mixed Integer ◽  
Real Case ◽  
Inventory Routing ◽  
Routing Problem ◽  
Content Type ◽  
Inventory Routing Problem ◽  
The Real ◽  
The Impact

Purpose In this paper, multi-period location–inventory–routing problem (LIRP) considering different vehicles with various capacities has been investigated for the supply chain of red meat. The purpose of this paper is to reduce variable and fixed costs of transportation and production, holding costs of red meat, costs of meeting livestock needs and refrigerator rents. Design/methodology/approach The considered supply chain network includes five echelons. Demand considered for each customer is approximated as deterministic using historical data. The modeling is performed on a real case. The presented model is a linear mixed-integer programming model. The considered model is solved using general algebraic modeling system (GAMS) software for data set of the real case. Findings A real-world case is solved using the proposed method. The obtained results have shown a reduction of 4.20 per cent in final price of red meat. Also, it was observed that if the time periods changed from month to week, the final cost of meat per kilogram would increase by 43.26 per cent. Originality/value This paper presents a five-echelon LIRP for the meat supply chain in which vehicles are considered heterogeneous. To evaluate the capability of the presented model, a real case is solved in Iran and its results are compared with the real conditions of a firm, and the rate of improvement is presented. Finally, the impact of the changed time period on the results of the solution is examined.

Stochastic inventory-routing problem with lateral transshipment for perishable product

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Parviz Fattahi ◽  
Mehdi Tanhatalab
Keyword(s):  
Supply Chain ◽  
Valid Inequalities ◽  
Upper And Lower Bounds ◽  
Inventory Routing ◽  
Routing Problem ◽  
Content Type ◽  
Inventory Routing Problem ◽  
Perishable Product ◽  
New Variant ◽  
Lateral Transshipment

Purpose This study aims to design a supply chain network in an uncertain environment while exists two options for distribution of the perishable product and production lot-sizing is concerned. Design/methodology/approach Owing to the complexity of the mathematical model, a solution approach based on a Lagrangian relaxation (LR) heuristic is developed which provides good-quality upper and lower bounds. Findings The model output is discussed through various examples. The introduction of some enhancements and using some heuristics results in better outputs in the solution procedure. Practical implications This paper covers the modeling of some real-world problems in which demand is uncertain and managers face making some concurrent decisions related to supply chain management, transportation and logistics and inventory control issues. Furthermore, considering the perishability of product in modeling makes the problem more practically significant as these days there are many supply chains handling dairy and other fresh products. Originality/value Considering uncertainty, production, transshipment and perishable product in the inventory-routing problem makes a new variant that has not yet been studied. The proposed novel solution is based on the LR approach that is enhanced by some heuristics and some valid inequalities that make it different from the current version of the LR used by other studies.

An M/M/C/K queueing system in an inventory routing problem considering congestion and response time for post-disaster humanitarian relief: a case study

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Mahdieh Masoumi ◽  
Amir Aghsami ◽  
Mohammad Alipour-Vaezi ◽  
Fariborz Jolai ◽  
Behdad Esmailifar
Keyword(s):  
Sensitivity Analyses ◽  
Inventory Routing ◽  
Humanitarian Relief ◽  
Exact Methods ◽  
Routing Problem ◽  
Content Type ◽  
Inventory Routing Problem ◽  
The People ◽  
Proposed Model

PurposeDue to the randomness and unpredictability of many disasters, it is essential to be prepared to face difficult conditions after a disaster to reduce human casualties and meet the needs of the people. After the disaster, one of the most essential measures is to deliver relief supplies to those affected by the disaster. Therefore, this paper aims to assign demand points to the warehouses as well as routing their related relief vehicles after a disaster considering convergence in the border warehouses.Design/methodology/approachThis research proposes a multi-objective, multi-commodity and multi-period queueing-inventory-routing problem in which a queuing system has been applied to reduce the congestion in the borders of the affected zones. To show the validity of the proposed model, a small-size problem has been solved using exact methods. Moreover, to deal with the complexity of the problem, a metaheuristic algorithm has been utilized to solve the large dimensions of the problem. Finally, various sensitivity analyses have been performed to determine the effects of different parameters on the optimal response.FindingsAccording to the results, the proposed model can optimize the objective functions simultaneously, in which decision-makers can determine their priority according to the condition by using the sensitivity analysis results.Originality/valueThe focus of the research is on delivering relief items to the affected people on time and at the lowest cost, in addition to preventing long queues at the entrances to the affected areas.

scholarly journals Inventory Routing Problem in Supply Chain of Perishable Products under Cost Uncertainty

Mathematics ◽  
2020 ◽  
Vol 8 (3) ◽  
pp. 382 ◽  
Author(s):  
Muhammad Imran ◽  
Muhammad Salman Habib ◽  
Amjad Hussain ◽  
Naveed Ahmed ◽  
Abdulrahman M. Al-Ahmari
Keyword(s):  
Mathematical Model ◽  
Supply Chain ◽  
Surgical Instruments ◽  
Perishable Products ◽  
Inventory Routing ◽  
Routing Problem ◽  
Cost Uncertainty ◽  
Priority Index ◽  
Inventory Routing Problem ◽  
Multi Objective

This paper presents a multi-objective, multi-period inventory routing problem in the supply chain of perishable products under uncertain costs. In addition to traditional objectives of cost and greenhouse gas (GHG) emission minimization, a novel objective of priority index maximization has been introduced in the model. The priority index quantifies the qualitative social aspects, such as coordination, trust, behavior, and long-term relationships among the stakeholders. In a multi-echelon supply chain, the performance of distributor/retailer is affected by the performance of supplier/distributor. The priority index measures the relative performance index of each player within the supply chain. The maximization of priority index ensures the achievement of social sustainability in the supply chain. Moreover, to model cost uncertainty, a time series integrated regression fuzzy method is developed. This research comprises of three phases. In the first phase, a mixed-integer multi-objective mathematical model while considering the cost uncertainty has been formulated. In order to determine the parameters for priority index objective function, a two-phase fuzzy inference process is used and the rest of the objectives (cost and GHG) have been modeled mathematically. The second phase involves the development of solution methodology. In this phase, to solve the mathematical model, a modified interactive multi-objective fuzzy programming has been employed that incorporates experts’ preferences for objective satisfaction based on their experiences. Finally, in the third phase, a case study of the supply chain of surgical instruments is presented as an example. The results of the case provide optimal flow of products from suppliers to hospitals and the optimal sequence of the visits of different vehicle types that minimize total cost, GHG emissions, and maximizes the priority index.

scholarly journals Identification, analysis and improvement of red meat supply chain strategies considering the impact of COVID-19 pandemic: a hybrid SWOT-QSPM approach in an emerging economy

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Farshid Riahi Dorcheh ◽  
Seyed Hossein Razavi Hajiagha ◽  
Misagh Rahbari ◽  
Vahid Jafari-Sadeghi ◽  
Hannan Amoozad Mahdiraji
Keyword(s):  
Supply Chain ◽  
Strategic Planning ◽  
Protein Product ◽  
Red Meat ◽  
Competitive Strategies ◽  
Content Type ◽  
The Right ◽  
The Impact ◽  
Beef Supply Chain

PurposeIn recent years, and especially during the coronavirus disease 2019 (COVID-19) pandemic, the significant role of agriculture, specifically red meat, in household consumption has been increased. On the other hand, the lack of proper policymaking in the production and pricing of red meat and the lack of a comprehensive study on the beef supply chain has led to a reduction in the role of this protein product in the household food basket. Thus, in this research, comprehensive strategic planning considering the effect of the COVID-19 pandemic has been illustrated to overcome the aforementioned problems.Design/methodology/approachTo study the intended objectives, first, using qualitative methods, the strengths, weaknesses, opportunities and threats (SWOT) to the studied company's supply chain in Iran were identified and then using the SWOT-Quantitative Strategic Planning Matrix (QSPM) technique, the surrounding strategies have been analysed.FindingsThe results indicate that the most important strength of the studied company is the “access to the red meat market of the retirement plan”; the most important weakness is the “lack of required and on-time funding, especially in the condition of the COVID-19 pandemic”; the highest-ranked opportunity is the “access to banking facilities” and the main threat to the company is the “COVID-19 pandemic limitations and health protocols”. In the same vein, by examining the attractiveness score of internal and external factors, it was observed that diversity and competitive strategies would have a higher priority. Finally, the QSPM illustrated that activating the full capacity of existing infrastructure has the highest priority.Originality/valueAccording to the red meat supply chain and the link amongst different market levels, identifying, analysing and improving the beef supply chain is of particular importance. One of the threats facing the international community is the emergence of events such as the COVID-19 pandemic, which requires businesses to choose the right strategy to deal with the issue. Therefore, the main distinction of this study is to identify, analyse and improve the red meat supply chain of a real case due to the condition of the COVID-19 pandemic.

A reliable location-inventory-routing three-echelon supply chain network under disruption risks

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Ehsan Mohebban-Azad ◽  
Amir-Reza Abtahi ◽  
Reza Yousefi-Zenouz
Keyword(s):  
Supply Chain ◽  
Objective Function ◽  
Problem Definition ◽  
Mixed Integer ◽  
Supply Chain Network ◽  
Inventory Routing ◽  
Content Type ◽  
Proposed Model ◽  
Disruption Risk ◽  
Disruption Risks

Purpose This study aims to design a reliable multi-level, multi-product and multi-period location-inventory-routing three-echelon supply chain network, which considers disruption risks and uncertainty in the inventory system. Design/methodology/approach A robust optimization approach is used to deal with the effects of uncertainty, and a mixed-integer nonlinear programming multi-objective model is proposed. The first objective function seeks to minimize inventory costs, such as ordering costs, holding costs and carrying costs. It also helps to choose one of the two modes of bearing the expenses of shortage or using the excess capacity to produce at the expense of each. The second objective function seeks to minimize the risk of disruption in distribution centers and suppliers, thereby increasing supply chain reliability. As the proposed model is an non-deterministic polynomial-time-hard model, the Lagrangian relaxation algorithm is used to solve it. Findings The proposed model is applied to a real supply chain in the aftermarket automotive service industry. The results of the model and the current status of the company under study are compared, and suggestions are made to improve the supply chain performance. Using the proposed model, companies are expected to manage the risk of supply chain disruptions and pay the lowest possible costs in the event of a shortage. They can also use reverse logistics to minimize environmental damage and use recycled goods. Originality/value In this paper, the problem definition is based on a real case; it is about the deficiencies in the after-sale services in the automobile industry. It considers the disruption risk at the first level of the supply chain, selects the supplier considering the parameters of price and disruption risk and examines surplus capacity over distributors’ nominal capacity.

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