Optimization via Simulation for Inventory Control Policies and Supplier Selection

Göçken, Mustafa; Dosdoğru, Ayşe Tuğba; Boru, Aslı

doi:10.2507/ijsimm16(2)5.375

Cited by 11 publications

(9 citation statements)

References 21 publications

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“…Many real life problems in optimization are too complex to be given tractable mathematical formulations. This difficulty gives rise to a remarkable growth in utilization of OvS methodology as a solution tool not only in academic world but also in practical settings [29][30][31]. The results reveal that OvS methodology is a promising candidate in the solution of challenging real life problems and expected to be well suited to a wide range of application areas.…”

Section: Discussionmentioning

confidence: 99%

Integrating Process Plan and Part Routing Using Optimization via Simulation Approach

Gocken¹,

Dosdogru²,

Boru³

et al. 2019

Int. j. simul. model.

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Determining the best process plan and route for each part is one of the main problems in dynamic stochastic systems. Therefore, multiple process plans are considered for each operation of each part (machine flexibility and/or part routing) and alternative operations (operation flexibility) simultaneously. In this paper, Optimization via Simulation (OvS) is utilized to plan the processes and route the parts in a dynamic stochastic flexible job-shop environment (DSFJS). Genetic algorithm (GA) which is envisaged to be the optimization component of OvS mechanism is integrated with the simulation model of the production system. A four-factor full factorial design is used to analyse the effect of main factors' and factor interactions' effects on the total of average flowtimes of each part performance of the shop. The design includes the flexibility level of the shop, number of parts, number of operations, and number of alternative process plans. Finally, the main findings of cases are summarized in the study.

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Section: Discussionmentioning

confidence: 99%

Integrating Process Plan and Part Routing Using Optimization via Simulation Approach

Gocken¹,

Dosdogru²,

Boru³

et al. 2019

Int. j. simul. model.

Self Cite

View full text Add to dashboard Cite

show abstract

“…In addition to simulation, optimization methods allow researchers to determine the best possible alternatives [29]. Hence, integrating simulation and optimization into the IRP ensures a remarkable solution method.…”

Section: Literature Reviewmentioning

confidence: 99%

A Novel Hybrid Artificial Intelligence Based Methodology for the Inventory Routing Problem

et al. 2019

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In this paper, a new hybrid method including simulation optimization and artificial intelligence based simulation is created to solve the inventory routing problem (IRP) in which three different routing strategies are evaluated for uneven demand patterns including intermittent, erratic, and lumpy demand. The proposed method includes two phases. In the first phase, a nondominated sorting genetic algorithm II based simulation is employed to perform a multi-objective search for the IRP where the objectives of the method are total supply chain cost minimization and average service level maximization. In the second phase, artificial neural network based simulation is used to adjust the reorder point and order-up-to-level by forecasting the customer demand at each replenishment time. The results of the study demonstrated that the average service level is at least 98.54% in the supply chain. From this, it can be concluded that the proposed method can provide a tremendous opportunity to improve the average service level under uncertain environments. In addition, it is determined that different routing strategies can be selected for different demand patterns according to the considered performance measures.

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“…Such practices include a wide range of operational and strategic activities like buyer-supplier relationship development, supply base leveraging and supplier performance evaluation [27,46]. With the growing need to establish long-term relationships with suppliers, certain issues regarding the adoption of quality management into these practices have been raised [32,15].…”

Section: Liteature Reviewmentioning

confidence: 99%

The Impact of Quality Management Purchasing Practices on Purchasing Performance in Transitional Economies

et al. 2019

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This study examines the nature of relationships between quality management practices in purchasing and purchasing-related organisational performance within ISO 9001:2008 environment in transitional economies. The study was based on managers' responses from 90 ISO 9001:2008 certified large organisations from Serbia. The findings show that quality management practices in purchasing positively affect purchasing performance. Further, purchasing performance is found to be a significant mediator between quality management practices and time-based performance. However, despite the overall good predictive model power, the explained variance on timebased performance is quite low. Thus, the effects on time-based performance are arguable. PLS-SEM Importance-performance analysis reveals that purchasing performance, cross-functional coordination and personnel management have relatively high performance, while benchmarking has the lowest value of the performance index. Consequently, the implementation of quality management practices in purchasing along with ISO 9001:2008 might be a part of a good strategic choice for transitional organisations to overcome troublesome transitional times. Still, the discrepancies between this study and the results from developed economies yield potential improvement areas on how organisations in transitional economies should manage purchasing practices.

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Optimization via Simulation for Inventory Control Policies and Supplier Selection

Cited by 11 publications

References 21 publications

Integrating Process Plan and Part Routing Using Optimization via Simulation Approach

Integrating Process Plan and Part Routing Using Optimization via Simulation Approach

A Novel Hybrid Artificial Intelligence Based Methodology for the Inventory Routing Problem

The Impact of Quality Management Purchasing Practices on Purchasing Performance in Transitional Economies

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