A genetic algorithm approach for multi-product multi-period continuous review inventory models

Saraçoğlu, İlkay; Topaloğlu, Şeyda; Keskintürk, Timur

doi:10.1016/j.eswa.2014.07.003

Cited by 41 publications

(20 citation statements)

References 37 publications

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“…Alaghebandha and Hajipour [11] presented a mathematical model for a multi-product continuous review inventory model and considered warehouse spaces, service level, number of shortages and cost of expected shortage limitations and finally used an ICA algorithm to solve the proposed model. Saracoglu et al [12] formulated a multi-product inventory models as an integer linear programming which considers some constraints such as capacity constraint and budget limitation and finally developed a genetic algorithm to solve their problem.…”

Section: Introductionmentioning

confidence: 99%

A bi-objective continuous review inventory control model: Pareto-based meta-heuristic algorithms

Fattahi

Hajipour

Nobari

2015

Applied Soft Computing

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Section: Introductionmentioning

confidence: 99%

A bi-objective continuous review inventory control model: Pareto-based meta-heuristic algorithms

Fattahi

Hajipour

Nobari

2015

Applied Soft Computing

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“…However, in this particular case, solutions based on genetic algorithms were defined since they are able to maintain a variety of possible solutions for every decision policy scenario. In fact, genetic algorithms find high quality solutions by selecting the best solution in each interaction (Chen, -589-Journal of Industrial Engineering and Management -http://dx.doi.org/10.3926/jiem.2090 Chen & Liang, 2016;Gunner, Tunali & Jans, 2010;Pelikan, 2010;Saracoglua, Topaloglub & Keskinturk, 2014). …”

Section: Methodsmentioning

confidence: 99%

Decision policy scenarios for just-in-sequence (JIS) deliveries

Cedillo-Campos¹,

Ruelas²,

Lizárraga-Lizárraga³

et al. 2017

JIEM

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Abstract:Purpose: The Just-in-Sequence (JIS) approach is evidencing advantages when controlling costs due to product variety management, and reducing the risk of disruption in sourcing, manufacturing companies and third-party logistics (3PL). This has increased its implementation in the manufacturing industry, especially in highly customized sectors such as the automotive industry. However, despite the growing interest from manufacturers, scholarly research focused on JIS still remains limited. In this context, little has been done to study the effect of JIS on the fluidity of supply chains and processes of logistics suppliers as well as providing them with a decision making tool to optimise the sequencing of their deliveries. Therefore, the aim of this paper is to propose a genetic algorithm to evaluate different decision policy scenarios to reduce risks of supply disruptions at assembly line of finished goods. Consequently, the proposed algorithm considers a periodic review of the inventory that assumes a steady demand and short response times is developed and applied.-581-Journal of Industrial Engineering and Management -http://dx.doi.org/10.3926/jiem.2090Design/methodology/approach: Based on a literature review and real-life information, an abductive reasoning was performed and a case study application of the proposed genetic algorithm conducted in the automotive industry. Findings:The results obtained from the case study indicate that the proposed genetic algorithm offers a reliable solution when facing variability in safety stocks that operate under assumptions such as: i) fixed costs; ii) high inventory turnover; iii) scarce previous information concerning material requirements; and iv) replenishment services as core business value. Although the results are based on an automotive industry case study, they are equally applicable to other assembly supply chains.Originality/value: This paper is of interest to practitioners and academicians alike as it complements and supports the very limited scholarly research on JIS by providing manufacturers and 3PL suppliers competing in mass customized industries and markets, a decision support system to help decision making. Implications for the design of modern assembly supply chains are also exposed and future research streams presented.

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“…Because, on the one hand a large part of organization's working capital be spent for purchasing goods and different materials, which may be exposed to waste and nothingness due to improper warehousing and mismanagement (Every year are witness for millions of monetary unit losses in this field in different organizations). On the other hand, unfortunately, the most exploits and the highest percentage of administrative and financial corruption lies in this field of management [2]. In order to avoid these risks and to prevent such damages, use and exploit of advanced purchasing and warehousing systems and applying proper management of goods and materials is inevitable [3,4].…”

Section: Introductionmentioning

confidence: 99%

Designing MRP Model in the Condition of Capacity Constraints and Variability of Delivery for Critical Items in ABC Inventory Model “Case Study in National Company of South’s Oil-rich”

Shoushtari¹,

Afsharkazemi²,

Radfar³

et al. 2017

Review Pub Administration Manag

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In productive enterprises, timely preparation and procurement of goods is very important due to that related costs to the production and working capitals of organization is severely affected. In available scientific methods, including MRP, regardless of resource constraints and other factors, the amount of lead time of goods has always considered to be fixed. In this paper, then a model will present that lead time of goods is considered as dynamic by using statistical and also effectiveness models from internal and external environment variables of organization and optimized the cost of production in order to reduce the latency in timely receiving and balancing the warehousing time. At the end, researcher with the implementation of issue in a simulated environment and compare it with the real environment, shows the advantage of proposed model compared to other models by numbers and figures.

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A genetic algorithm approach for multi-product multi-period continuous review inventory models

Cited by 41 publications

References 37 publications

A bi-objective continuous review inventory control model: Pareto-based meta-heuristic algorithms

A bi-objective continuous review inventory control model: Pareto-based meta-heuristic algorithms

Decision policy scenarios for just-in-sequence (JIS) deliveries

Designing MRP Model in the Condition of Capacity Constraints and Variability of Delivery for Critical Items in ABC Inventory Model “Case Study in National Company of South’s Oil-rich”

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