Coordination policy for production and delivery scheduling in the closed loop supply chain

Goli, Alireza; Davoodi, Sayyed Mohammad Reza

doi:10.1007/s11740-018-0841-0

Cited by 28 publications

(17 citation statements)

References 23 publications

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“…Constraints of the developed mathematical model in the metaheuristic algorithm. In the course of designing an algorithm for solving an optimization problem, most attention should be paid to the problem constraints and its feasible space [13,14]. The product portfolio optimization problem considered in this study includes the following three constraints.…”

Section: 3mentioning

confidence: 99%

Application of robust optimization for a product portfolio problem using an invasive weed optimization algorithm

Goli¹,

Zare²,

Tavakkoli–Moghaddam³

et al. 2019

Numerical Algebra, Control &Amp; Optimization

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Product portfolio optimization (PPO) is a strategic decision for many organizations. There are several technical methods for facilitating this decision. According to the reviewed studies, the implementation of the robust optimization approach and the invasive weed optimization (IWO) algorithm is the research gap in this field. The contribution of this paper is the development of the PPO problem with the help of the robust optimization approach and the multi-objective IWO algorithm. Considering the profit margin uncertainty in real-world investment decisions, the robust optimization approach is used to address this issue. To illustrate the real-world applicability of the model, it is implemented for dairy products of Pegah Golpayegan Company in Iran. The numerical results obtained from the IWO algorithm demonstrate the effectiveness of the proposed algorithm in tracing out the efficiency frontier of the product portfolio. The average risk of efficient frontier solutions in the deterministic model is about 0.4 and for the robust counterpart formulation is at least 0.5 per product. The efficient frontier solutions obtained from robust counterpart formulation demonstrate a more realistic risk level than the deterministic model. The comparisons between CPLEX, IWO and genetic algorithm (GA) shows that the performance of the IWO algorithm is much better than the older algorithms and can be considered as an alternative to algorithms, such as GA in product portfolio optimization problems.

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Section: 3mentioning

confidence: 99%

Application of robust optimization for a product portfolio problem using an invasive weed optimization algorithm

Goli¹,

Zare²,

Tavakkoli–Moghaddam³

et al. 2019

Numerical Algebra, Control &Amp; Optimization

Self Cite

View full text Add to dashboard Cite

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“…The origin of SA is the works of Carrick Patrick et al and Kearney et al in 1983 and 1985, respectively. Carrick Patrick et al were specialists in statistical physics, who proposed a method based on gradual annealing technique to solve difficult optimization problems (Goli and Davoodi, 2018). The gradual annealing technique is used by metallurgists to reach a state where the solid material is well-structured and its energy is minimized.…”

Section: Methodsmentioning

confidence: 99%

Performance of different hybrid algorithms for prediction of wind speed behavior

et al. 2019

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This study seeks to provide a new method by proposing three hybrid algorithms. The proposed algorithms include genetic neural network hybrid algorithm, simulated annealing neural network hybrid algorithm, and shuffled frog-leaping neural network hybrid algorithm. The efficiency and reliability of the presented hybrid algorithms in prediction of wind speed behavior were evaluated using meteorological data of the city of Abadeh for a 10-year period from 2005 to 2015. The forecasting horizon is monthly for this study. The study parameters consisted of TMAX, TMIN, VP, RHMIN, RHMAX, WIND SPEED, PRECIPITATION, and SUNSHINE HOURS. These eight parameters are used as the inputs, and one parameter (ET) is used as the output. Research findings show that the shuffled frog-leaping neural network hybrid algorithm providing a root mean square error value of 0.0761 and reliability of 0.91 is more suitable than other hybrid algorithms for prediction of wind speed behavior in the study area.

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“…Equation (29) points out that each distribution center can only be established at a single capacity level. Equations (30) to (32) state that if one of the distributions, hybrid, or disposal centers is established in period t-1, it should be activated in the next periods.…”

Section: Physical Flow Constraintsmentioning

confidence: 99%

“…With the help of this simple concept, a new field of mathematics and computational theory has emerged, which encompasses many applications in various fields of science, including control systems, machine vision, and artificial intelligence. 30 For a membership function, there are different choices that can be chosen depending on the intended application. In a general classification given by Zadeh, 27 fuzzy functions can be classified into two linear and nonlinear groups.…”

Section: Fuzzy Set Definitionmentioning

confidence: 99%

Multiobjective fuzzy mathematical model for a financially constrained closed‐loop supply chain with labor employment

Goli

Zare

Tavakkoli‐Moghaddam

et al. 2019

Computational Intelligence

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This paper addresses the multiobjective, multiproducts and multiperiod closed‐loop supply chain network design with uncertain parameters, whose aim is to incorporate the financial flow as the cash flow and debts' constraints and labor employment under fuzzy uncertainty. The objectives of the proposed mathematical model are to maximize the increase in cash flow, maximize the total created jobs in the supply chain, and maximize the reliability of consumed raw materials. To encounter the fuzzy uncertainty in this model, a possibilistic programming approach is used. To solve large‐sized problems, the multiobjective simulated annealing algorithm, multiobjective gray wolf optimization, and multiobjective invasive weed optimization are proposed and developed. The numerical results demonstrate that these algorithms solve the problems within about 1% of the required solving time for the augmented ε‐constraint and have similar performance and even better in some cases. The multiobjective simulated annealing algorithm with a weak performance takes less time than the other two algorithms. The multiobjective gray wolf optimization and multiobjective invasive weed optimization algorithms are superior based on the multiobjective performance indices.

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Coordination policy for production and delivery scheduling in the closed loop supply chain

Cited by 28 publications

References 23 publications

Application of robust optimization for a product portfolio problem using an invasive weed optimization algorithm

Application of robust optimization for a product portfolio problem using an invasive weed optimization algorithm

Performance of different hybrid algorithms for prediction of wind speed behavior

Multiobjective fuzzy mathematical model for a financially constrained closed‐loop supply chain with labor employment

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