A De Novo programming approach for a robust closed-loop supply chain network design under uncertainty: An M/M/1 queueing model

Saeedi, Sarow; Mohammadi, Mohammad; Torabi, S. Ali

doi:10.5267/j.ijiec.2014.11.002

Cited by 20 publications

(12 citation statements)

References 23 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…DNP not only obtains optimal resource integration but also promotes the conceptual of strategic alliances for firm"s cooperation between each other. [39] presented the capacity determination in a closed-loop SC network when a queuing system is established in the reverse flow. Since the queuing system imposes costs, the decision maker faces the challenge to determine the capacity of facilities which represent a compromise between the queuing costs and the fixed costs of opening new facilities.They developed DNP approach to determine the capacity of recovery facilities in the reverse flow using a mixed integer nonlinear programming model integrated with the DNP and uncertainty of the parameters.…”

Section: A Historical Review Over De Novo Programmingmentioning

confidence: 99%

The Literature Review of De Novo Programming

Hassan¹

2021

JUSST

View full text Add to dashboard Cite

De novo programming (DNP) is a system design approach which links system flexibility efficient and optimal system design. It shows that within single or multi-objective decision making framework. DNP allows the decision maker to achieve an ideal or meta-optimal system performance, or improve the performance of compromise solutions through the modification of the feasible region of decision alternatives. This paper considers a brief review of DNP, which provides a brief insight DNP and its applications.

show abstract

Section: A Historical Review Over De Novo Programmingmentioning

confidence: 99%

The Literature Review of De Novo Programming

Hassan¹

2021

JUSST

View full text Add to dashboard Cite

show abstract

“…Vahdani et al [31] applied queue system for a bi-objective SC problem including total costs and unforeseen transportation costs and used a robust optimization (RO) approach to face with uncertain parameters. Saeedi et al [32] developed an uncertain model for a CLSC problem and tried to set a balance between queue costs and other costs of system to determine the capacity of facilities. Vahdani and Mohammadi [33] formulated an uncertain SC problem and used queue system to decrease the processing time.…”

Section: Queue System and Uncertainty In Supply Chainmentioning

confidence: 99%

“…The constraint (31) describes that the load of a vehicle remains constant when the vehicle does not meet the retailer u. The constraint (32) shows the minimum and maximum limitation of loads for a vehicle to visit the retailors. The constraint (33) determines how many vehicles are needed to ship the returned items from retailor (w) to RC (r).…”

mentioning

confidence: 99%

A hybrid metaheuristic algorithm for a data driven leagile sustainable closed-loop supply chain model under disruption risks

2020

View full text Add to dashboard Cite

In the current situation, taking into consideration the environmental and social issues are related with the production and distribution of products in supply chain systems, due to the global concerns related with emitting lots of greenhouse gases within the manufacturing process and overlooking the major needs of public. This paper proposes a new multi objective model in the area of closed loop supply chain problem integrated with lot sizing by considering lean, agility and sustainability factors simultaneously. Next, a robust possibilistic programming approach is applied to handle the uncertainty of the model. To increase the responsiveness of the system, a fuzzy c-means clustering method is applied to select the potential locations based on the proximity to local customers. In the following, a new hybrid metaheuristic algorithm is developed to deal with large size problems efficiency and to assess the impact of using a single-based initial solution as the income for the second phase of the proposed hybrid algorithm. To ensure about the effectiveness of the proposed algorithm, another well-known metaheuristic algorithm is developed too. The results reached from experiments on different test problems approve the superiority of the hybrid metaheuristic algorithm to find better solutions.

show abstract

“…They found that for different scenarios, a single product, single period will perform well with constant demand and uncertain returns. In another study Saeedi, Mohammadi and Torabi (2015) has studied the capacity determination in CLSC by establishing the queue system. Here the queue cost and fixed opening cost are obtained by modeling a mixed integer nonlinear programming.…”

Section: Literature Reviewmentioning

confidence: 99%

Optimal inventory policy in a closed loop supply chain system with multiple periods

Arumugam

Natarajan

Sapabathy

et al. 2017

JIEM

View full text Add to dashboard Cite

Abstract:Purpose: This paper aims to model and optimize the closed loop supply chain for maximizing the profit by considering the fixed order quantity inventory policy in various sites at multiple periods.Design/methodology/approach: In forward supply chain, a standard inventory policy can be followed when the product moves from manufacturer, distributer, retailer and customer but the inventory in the reverse supply chain of the product with the similar standard policy is very difficult to manage. This model investigates the standard policy of fixed order quantity by considering the three major types of return-recovery pair such as commercial returns, end-ofuse returns, end -of-life returns and their inventory positioning at multiple periods. The model is configured as mixed integer linear programming and solved by IBM ILOG CPLEX OPL studio. Findings:To find the performance of the model a numerical example is considered for a product with three Parts (A which of 2nos, B and C) for 12 multiple periods. The results of the analysis show that the manufacturer can know how much should to be manufacture in multiple periods based on Variations of the demand by adopting the FOQ inventory policy at different sites considering its capacity constraints. In addition, it is important how much of parts should be purchased from the supplier at the given 12 periods.-237-Journal of Industrial Engineering and Management -https://doi.org/10.3926/jiem.2205 Originality/value: A sensitivity analysis is performed to validate the proposed model two parts.First part of the analysis will focus on the inventory of product and parts and second part of analysis focus on profit of the company. The analysis which provides some insights in to the structure of the model.

show abstract

A De Novo programming approach for a robust closed-loop supply chain network design under uncertainty: An M/M/1 queueing model

Cited by 20 publications

References 23 publications

The Literature Review of De Novo Programming

The Literature Review of De Novo Programming

A hybrid metaheuristic algorithm for a data driven leagile sustainable closed-loop supply chain model under disruption risks

Optimal inventory policy in a closed loop supply chain system with multiple periods

Contact Info

Product

Resources

About