Hybrid heuristic for the location‐inventory‐routing problem in closed‐loop supply chain

2018 ◽  
Vol 28 (3) ◽  
pp. 1265-1295 ◽  
Author(s):  
Qunli Yuchi ◽  
Nengmin Wang ◽  
Zhengwen He ◽  
Haoxun Chen
Keyword(s):  
Supply Chain ◽  
Closed Loop ◽  
Inventory Routing ◽  
Closed Loop Supply Chain ◽  
Routing Problem ◽  
Hybrid Heuristic ◽  
Inventory Routing Problem

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 A Nonlinear Integer Programming Model for Integrated Location, Inventory, and Routing Decisions in a Closed-Loop Supply Chain

Complexity ◽  
2018 ◽  
Vol 2018 ◽  
pp. 1-17 ◽  
Author(s):  
Hao Guo ◽  
Congdong Li ◽  
Ying Zhang ◽  
Chunnan Zhang ◽  
Yu Wang
Keyword(s):  
Supply Chain ◽  
Integer Programming ◽  
Facility Location ◽  
Vehicle Routing ◽  
Closed Loop ◽  
Programming Model ◽  
Nonlinear Integer Programming ◽  
Inventory Routing ◽  
Closed Loop Supply Chain ◽  
Integer Programming Model

Facility location, inventory management, and vehicle routing are three important decisions in supply chain management, and location-inventory-routing problems consider them jointly to improve the performance and efficiency of today’s supply chain networks. In this paper, we study a location-inventory-routing problem to minimize the total cost in a closed-loop supply chain that has forward and reverse logistics flows. First, we formulate this problem as a nonlinear integer programming model to optimize facility location, inventory control, and vehicle routing decisions simultaneously in such a system. Second, we develop a novel heuristic approach that incorporates simulated annealing into adaptive genetic algorithm to solve the model efficiently. Last, numerical analysis is presented to validate our solution approach, and it also provides meaningful managerial insight into how to improve the closed-loop supply chain under study.

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.

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