Optimizing a multi-vendor multi-retailer vendor managed inventory problem: Two tuned meta-heuristic algorithms

Sadeghi, Javad; Mousavi, Seyed Mohsen; Niaki, Seyed Taghi Akhavan; Sadeghi, Saeid

doi:10.1016/j.knosys.2013.06.006

Cited by 91 publications

(45 citation statements)

References 46 publications

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“…Recent investigations in [73][74][75][76] have shown that hybrid meta-heuristics work better than individual meta-heuristics in solving mixed integer or nonlinear models. Commonly, hybridization refers to the mixture of two search algorithms to solve a given problem [75].…”

Section: The Hybrid Solution Algorithmsmentioning

confidence: 99%

A flexible cell scheduling problem with automated guided vehicles and robots under energy-conscious policy

2017

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Abstract. A exible Cell Scheduling Problem (CSP) under Time-Of-Use (TOU)electricity tari s is developed in this study. To apply a kind of energy-conscious policy, overconsumption cost of on-peak period electricity, limitations on total energy consumption by all facilities, setup time available on each cell, part defect (pert) percentage, and the total number of Automated Guided Vehicles (AGV) were considered. Additionally, an Ant Colony Optimization (ACO) algorithm was employed to nd a near-optimum solution to the proposed Mixed Integer Linear Programming (MILP) model with the objective of minimizing the total cost of CSP model. Since no benchmark is available in the literature, a lower bound was implemented as well to validate the result achieved. Moreover, to improve the quality of the results obtained by meta-heuristic algorithms, two hybrid algorithms (HGA and HACO) were proposed to solve the model. For parameter tuning of algorithms, Taguchi experimental design method was applied. Then, numerical examples were presented to prove the application of the proposed methodology. Our results were compared with the lower bound, con rming consequently that HACO is capable of nding better and near-optimum solutions.

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Section: The Hybrid Solution Algorithmsmentioning

confidence: 99%

A flexible cell scheduling problem with automated guided vehicles and robots under energy-conscious policy

2017

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“…Taleizadeh et al [14] developed a multi-product model with a singlevendor, multi-buyer with variable lead time. Sadeghi et al [15] developed a constrained MV-MR-SW, SC in which both the space and annual number of orders of the central warehouse are limited. The goal is to nd the order quantities along with the number of shipments received by retailers and vendors so that the total inventory cost of the chain can be minimized.…”

Section: Literature Reviewmentioning

confidence: 99%

“…Constraints (15) and (16) show delivery quantity and inventory levels which should be equal to the capacity of manufacturers and distributors, so delivery quantities are less than or equal to capacities represented in Constraints (17) and (18). Constraint (19) shows that delivery quantity from distribution centers to customers is equal to or less than customers' demands.…”

Section: Mathematical Formulations Of Modelmentioning

confidence: 99%

A fuzzy dynamic multi-objective, multi-item model by considering customer satisfaction in supply chain

et al. 2017

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Abstract. Customer satisfaction is an important issue in competitive strategic management of companies. Logistical and cross-functional drivers of supply chain have an important role in managing customer satisfaction. Customer satisfaction depends on quality, cost, and delivery. In this paper, a fuzzy mixed integer nonlinear programming model is proposed for a multi-item multi-period problem in a multi-level supply chain. Minimization of costs, manufacturing and transportation time, transportation risks, maximization of quality by minimizing the number of defective products, and maximization of customers' service levels are considered to be objective functions of the model. Furthermore, it is assumed that the demand rates are fuzzy values. An exact "-constraint approach is used to solve the problem. The problem is computationally intractable. Therefore, the Non-dominant Sorting Genetic Algorithm (NSGA-II) is developed to solve it. The Taguchi method is utilized to tune the NSGA-II parameters. Finally, some numerical examples are generated and solved to evaluate the performance of the proposed model and solving methods.

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“…Nia et al (2014) developed a fuzzy VMI of multi-item EOQ model under shortage and solved the resulted model using an ant colony optimization algorithm. According to Sadeghi et al (2013), the VMI is a common policy in SCM to reduce bullwhip effects. There are various applications of VMI proposed in the literature but limited works focused on the multi-vendor multi-retailer single-warehouse (MV-MR-SW) case.…”

Section: Introductionmentioning

confidence: 99%

“…There are various applications of VMI proposed in the literature but limited works focused on the multi-vendor multi-retailer single-warehouse (MV-MR-SW) case. Sadeghi et al (2013) developed a constrained MV-MR-SW supply chain, in which both the space and the annual number of orders of the central warehouse were limited. They formulated the model and used particle swarm optimization (PSO) to determine an approximate optimum solution of the problem.…”

Section: Introductionmentioning

confidence: 99%

Vendor managed inventory in multi level supply chain

Bani-Asadi¹,

Zanjani²

2017

10.5267/j.dsl

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Vendor managed inventory (VMI) is one of the most effective methods for reducing bullwhip effect. This paper presents a mathematical VMI model where there are three levels of central storage, multi distribution centers and various retailors. The problem is formulated as a mixed integer programming by considering uncertainty on different input parameters. To cope with uncertainty, the study uses rectangular fuzzy numbers. We also propose two metaheuristics; namely, genetic algorithm and particle swarm optimization to solve the resulted problems for some large instances. The preliminary results have indicated that genetic algorithm could solve the proposed model faster than particle swarm optimization in terms of CPU time reaching to slightly better objective functions.Growing Science Ltd. All rights reserved. 7

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Optimizing a multi-vendor multi-retailer vendor managed inventory problem: Two tuned meta-heuristic algorithms

Cited by 91 publications

References 46 publications

A flexible cell scheduling problem with automated guided vehicles and robots under energy-conscious policy

A flexible cell scheduling problem with automated guided vehicles and robots under energy-conscious policy

A fuzzy dynamic multi-objective, multi-item model by considering customer satisfaction in supply chain

Vendor managed inventory in multi level supply chain

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