Robust and fuzzy goal programming optimization approaches for a novel multi-objective hub location-allocation problem: A supply chain overview

Ghodratnama, Ali; Tavakkoli–Moghaddam, Reza; Azaron, Amir

doi:10.1016/j.asoc.2015.07.038

Cited by 49 publications

(30 citation statements)

References 59 publications

(89 reference statements)

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“…This gap has also existed in optimization models as well as another field of engineering (Ehrgott et al, 2014;Gabrel et al, 2014;Goerigk & Schöbel, 2015;Wang & Shan, 2007). (Ghodratnama et al, 2015) √ √ √ √ √ √ 16 (Pishvaee & Fazli Khalaf, 2016 (Gul & Zoubir, 2017) √ √ √ 33 (Goerigk & Schöbel, 2015) √ √ √ √ √ 34 (Gorissen, 2015) √ √ √ √ √ √ 35 (Liu et al, 2015) √ √ √ √ 36 (Sun et al, 2015) √ √ √ 37 √ √ √ √ 38 (Wu , 2015) √ √ √ √ √ 39 (Khan et al, 2015) √ √ √ 40 (Park, 2016) √ √ √ 41 (Goberna et al, 2015) √ √ √ √ 42 √ √ √ 43 (Wang & Pedrycz, 2015) √ √ √ √ √ 44 (Yu & Zeng, 2015) √ √ √ 45 (Asafuddoula et al, 2015) √ √ √ √ √ √ 46 (Dellino et al, 2015) √ √ √ √ √ √ √ √ √ 47 (Auzins et al, 2015) √ √ √ √ √ √ 48 (Cao et al, 2015) √ √ √ √ √ √ 49 (Ng et al, 2015) √ √ √ √ √ √ √ 50 (Allahverdi, 2015) √ √ …”

Section: Discussionmentioning

confidence: 99%

An overview on robust design hybrid metamodeling: Advanced methodology in process optimization under uncertainty

Parnianifard¹,

Azfanizam²,

Ariffin³

et al. 2018

10.5267/j.ijiec

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Nowadays, process optimization has been an interest in engineering design for improving the performance and reducing cost. In practice, in addition to uncertainty or noise parameters, a comprehensive optimization model must be able to attend other circumstances which might be imposed in problems under real operational conditions such as dynamic objectives, multiresponses, various probabilistic distribution, discrete and continuous data, physical constraints to design parameters, performance cost, computational complexity and multi-process environment. The main goal of this paper is to give a general overview on topics with brief systematic review and concise discussions about the recent development on comprehensive robust design optimization methods under hybrid aforesaid circumstances. Both optimization methods of mathematical programming based on Taguchi approach and robust optimization based on scenario sets are briefly described. Metamodels hybrid robust design is discussed as an appropriate methodology to decrease computational complexity in problems under uncertainty. In this context, the authors' policy is to choose important topics for giving a systematic picture to those who wish to be more familiar with recent studies about robust design optimization hybrid metamodels, also by attending real circumstances in practice. In particular, production and project management are considered as two important methodologies that could be improved by applications of advanced robust design combining with metamodel methods.

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Section: Discussionmentioning

confidence: 99%

An overview on robust design hybrid metamodeling: Advanced methodology in process optimization under uncertainty

Parnianifard¹,

Azfanizam²,

Ariffin³

et al. 2018

10.5267/j.ijiec

View full text Add to dashboard Cite

show abstract

“…It can be seen that the raising volatility will increase the expected value of CWT. Therefore, the expected value of CWT in Mode 2 is able to be obtained by (7). Considering the completeness of raw materials distribution, the CWT in Mode 1 is relatively complex.…”

Section: The Flexibility Assessment Of Two Distribution Modes In the mentioning

confidence: 99%

“…(ii) Optimization of logistics network: Ghodratnama et al [7] proposed a single distribution hub location model with the objective of total transportation and installation costs and also considered the effects of different modes of transport on greenhouse gas emissions. Yang et al [8] used the new fuzzy random simulation technique and the multistart simulated annealing algorithm to optimize the intermodal hub-andspoke model to obtain the minimum mixed traffic cost and travel time.…”

Section: Introductionmentioning

confidence: 99%

A Flexible Logistics Distribution Hub Model considering Cost Weighted Time

Ran

Zhang

Liu

2017

Discrete Dynamics in Nature and Society

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The delivery time of order has become an important fact for customers to evaluate logistics services. Due to the diverse and large quantities of orders in the background of electronic commerce, how to improve the flexibility of distribution hub and reduce the waiting time of customers becomes one of the most challenging questions for logistics companies. With this in mind, this paper proposes a new method of flexibility assessment in distribution hub by introducing cost weighted time (CWT). The advantages of supply hub operation mode in delivery flexibility are verified by the approach: the mode has pooling effects and uniform distribution characteristics; these traits can reduce overlapping delivery time to improve the flexibility in the case of two suppliers. Numerical examples show that the supply hub operation mode is more flexible than decentralized distribution operation mode in multidelivery cycles.

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“…Constraint (26) ensures that the production quantity of each paper type not to exceed the production capacity of the new paper manufacturers. Capacities of centralized collection centers are restricted by Constraint (27). Constraint (28) to (30) ensure that the sum of the waste paper taken from a centralized collection point to recycling facilities, energy recovery centers and disposal sites do not exceed the amount of waste paper available at the centralized collection center.…”

Section: Max Z P W MV F W Dv F W Cv F W Rv Fmentioning

confidence: 99%

“…Step 7: This step proposes an FGP approach [27] to attain the most preferable compromise solution for the multiobjective problem. Construct the FGP formulation as follows:…”

Section: Proposed Hybrid Solution Approachmentioning

confidence: 99%

Closed loop supply chain network design for the paper industry: A multi-objective stochastic robust approach

et al. 2017

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Closed loop supply chain design is to provide an optimal platform for efficient and effective supply chain management. It is an essential and strategic operation management problem in supply chain management, and usually includes multiple and conflicting objectives. A new mixed integer non-linear programming model for a multi-objective closed loop supply chain network design problem in the paper industry is developed under uncertainty. The objective functions are to minimize the total cost, maximize the total volume flexibility and minimize the total number of vehicles hired in order to fulfill the paper industry's policies towards a cleaner and green environment. Also, a novel hybrid solution is presented based on stochastic programming, robust optimization and fuzzy goal programming. A numerical example utilizing the real data from the paper industry in East Azerbaijan of Iran is designed and the model performance is assessed. Furthermore, a recently developed Dragonfly Algorithm (DA) employed to solve the given problem in large scales and compared with Genetic Algorithm (GA). The results indicated that the DA achieved better performance compared with the GA.

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Robust and fuzzy goal programming optimization approaches for a novel multi-objective hub location-allocation problem: A supply chain overview

Cited by 49 publications

References 59 publications

An overview on robust design hybrid metamodeling: Advanced methodology in process optimization under uncertainty

An overview on robust design hybrid metamodeling: Advanced methodology in process optimization under uncertainty

A Flexible Logistics Distribution Hub Model considering Cost Weighted Time

Closed loop supply chain network design for the paper industry: A multi-objective stochastic robust approach

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