scholarly journals Green Inventory Routing Problem using Hybrid Genetic Algorithm

2021 ◽  
Vol 6 (4) ◽  
pp. 10-19
Author(s):  
Huda Zuhrah Ab Halim ◽  
Nureffa Natasha Mohd Azliana ◽  
Nuridawati Baharom ◽  
Nur Fatihah Fauzi ◽  
Nurizatul Syarfinas Ahmad Bakhtiar ◽  
...  
Keyword(s):  
Carbon Dioxide ◽  
Genetic Algorithm ◽  
Supply Chain ◽  
Fuel Consumption ◽  
Hybrid Genetic Algorithm ◽  
Inventory Routing ◽  
Routing Problem ◽  
Total Cost ◽  
Inventory Routing Problem ◽  
Consumption Cost

Carbon dioxide (CO2) is known as one of the largest sources of global warming. One of the ways to curb CO2 emissions is by considering the environmental aspect in the supply chain management. This paper analyses the influence of carbon emissions on the Inventory Routing Problem (IRP). The IRP network consists of a depot, an assembly plant and multiple suppliers. The deterministic demands vary and are determined by the assembly plant. Fixed transportation cost, fuel consumption cost and inventory holding cost are used to evaluate the system’s total cost in which fuel consumption cost is determined by fuel consumption rate, distance, and fuel price. Backordering and split pick-up are not allowed. The main purpose of this study is to analyze the distribution network especially the overall costs of the supply chain by considering the CO2 emissions as well. The problem is known as Green Inventory Routing Problem (GIRP). The mixed-integer linear programming of this problem is adopted from Cheng et al. wherein this study a different Hybrid Genetic Algorithm is proposed at mutation operator. As predicted, GIRP has a higher total cost as it considered fuel consumption cost together with the transportation and inventory costs. The results showed the algorithm led to different sequences of routings considering the carbon dioxide emission in the objective function.

scholarly journals The Location Inventory Routing Optimization Model and Algorithm for the Islands Shipping Network

2021 ◽  
Author(s):  
Di Wu ◽  
Nuo Wang
Keyword(s):  
Genetic Algorithm ◽  
Sensitivity Analysis ◽  
Hybrid Genetic Algorithm ◽  
Construction Cost ◽  
Inventory Routing ◽  
Routing Problem ◽  
Hub And Spoke ◽  
Total Cost ◽  
Routing Optimization ◽  
Practical Information

Abstract This paper studies a hub-and-spoke shipping network of islands and integrates a maritime location inventory routing problem (MLIRP) for the islands shipping network. By determining a series of decisions including the location of the hub islands, the number of shipping routes, the schedule of every route, the running mode of every route, the ship size, the wharf scale and the inventory capacity, the objective of the paper is to minimize the total cost of the islands shipping network. For solving the integrated MLIRP model, a hybrid genetic algorithm based on the stepwise configuration (SC-GA) is presented. Finally, instances are put forward to evaluate the performance of the algorithm. The results of sensitivity analysis show that the wharf construction cost affects the total costs the most, so more attention should be paid to it when making decisions. This paper can provide theoretical and practical information to design and optimize an islands shipping network.

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.

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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