Optimizing multi-item multi-period inventory control system with discounted cash flow and inflation: Two calibrated meta-heuristic algorithms

Mousavi, Seyed Mohsen; Hajipour, Vahid; Niaki, Seyed Taghi Akhavan; Alikar, Najmeh

doi:10.1016/j.apm.2012.05.019

Cited by 88 publications

(35 citation statements)

References 31 publications

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“…This method attempts to minimize the noise e ect and determine an optimal level of signal factors using signal to noise ratio [48][49]. Table 3 indicates di erent levels of factors for MOICA and NSGA-II [50].…”

Section: Results Analysismentioning

confidence: 99%

Integrated and Dynamic Design of Sustainable Closed-loop Supply Chain Network Considering Pricing

Nobari

Kheirkhah

2017

Scientia Iranica

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KEYWORDSDynamic supply chain network design; Integrated planning; Sustainability; Pricing; Pareto-based multi-objective metaheuristic algorithm.Abstract. In this paper, a novel multi-objective model for dynamic and integrated network design of sustainable closed-loop supply chain network is proposed, which aims to optimize economic, environmental, and social concerns, simultaneously. In order to have a dynamic design, multiple strategic periods are considered during the planning horizon. Furthermore, di erent short-term decisions are integrated with long-term decisions related to the network design problem. Two of these short-term decisions determine selling price of products in forward logistics and buying price of used products from customer zones in reverse logistics. Due to the complexity of the proposed multi-objective model, a MultiObjective Imperialist Competitive Algorithm (MOICA) is proposed to solve the model, and the results are compared with a non-dominated sorting genetic algorithm (NSGA-II). Finally, to evaluate the performance of proposed algorithm, several numerical examples are used of which the results indicate the e ciency of the proposed algorithm.

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Section: Results Analysismentioning

confidence: 99%

Integrated and Dynamic Design of Sustainable Closed-loop Supply Chain Network Considering Pricing

Nobari

Kheirkhah

2017

Scientia Iranica

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“…In the VDO algorithm, at high amplitudes, the solution scope is larger and a new solution is more likely to be obtained. Therefore, when the amplitude is reduced, the probability of obtaining a new solution decreases; then the trend continues until the amplitude fades away [32,36].…”

Section: Movdo Main Loopmentioning

confidence: 99%

Bi-objective vibration damping optimization for congested location–pricing problem

Hajipour

Farahani

2016

Computers & Operations Research

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This paper presents a bi-objective mathematical programming model for the restricted facility location problem, under a congestion and pricing policy. Motivated by various applications such as locating server on internet mirror sites and communication networks, this research investigates congested systems with immobile servers and stochastic demand as M/M/m/k queues. For this problem, we consider two simultaneous perspectives; (1) customers who desire to limit waiting time for service and (2) service providers who intend to increase profits. We formulate a bi-objective facility location problem with two objective functions: (i) maximizing total profit of the whole system and (ii) minimizing the sum of waiting time in queues; the model type is mixed-integer nonlinear. Then, a multi-objective optimization algorithm based on vibration theory (so-called multi-objective vibration damping optimization (MOVDO)), is developed to solve the model. Moreover, the Taguchi method is also implemented, using a response metric to tune the parameters.The results are analyzed and compared with a non-dominated sorting genetic algorithm (NSGA-II) as a well-developed multi-objective evolutionary optimization algorithm. Computational results demonstrate the efficiency of the proposed MOVDO to solve large-scale problems.

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“…There are two suggested ways in Taguchi method to analyze the results. First, analysis of variance that is used for experiments that are repeated once; second, Signalto-Noise ratio (S=N) that is used for experiments with multiple runs [36]. In the second method, a statistical measurement, S=N, is used to evaluate the performance.…”

Section: Mutation Operatormentioning

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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Optimizing multi-item multi-period inventory control system with discounted cash flow and inflation: Two calibrated meta-heuristic algorithms

Cited by 88 publications

References 31 publications

Integrated and Dynamic Design of Sustainable Closed-loop Supply Chain Network Considering Pricing

Integrated and Dynamic Design of Sustainable Closed-loop Supply Chain Network Considering Pricing

Bi-objective vibration damping optimization for congested location–pricing problem

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

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