Bi-Level Multi-Objective Production Planning Problem with Multi-Choice Parameters: A Fuzzy Goal Programming Algorithm

Kamal, Murshid; Gupta, Srikant; Chatterjee, Prasenjit; Pamučar, Dragan; Stević, Željko

doi:10.3390/a12070143

Cited by 12 publications

(5 citation statements)

References 44 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The functional parameters taken into account during the optimization process are: (a) motor efficiency, (b) power factor and (c) starting capability. In an elaborated algorithm, the optimization problem with many objectives has been transformed to a single objective function consisting of all objectives [6,25,26]. Such an approach is known from the linear programming method.…”

Section: Formulation Of the Design Problemmentioning

confidence: 99%

Optimization of Low-Power Line-Start PM Motor Using Gray Wolf Metaheuristic Algorithm

Knypiński

Pawełoszek

Menach³

2020

Energies

View full text Add to dashboard Cite

The paper presents the optimization method and computer software for the design of a low-power line-start permanent magnet synchronous motor (LSPMSM). The in-house-developed computer software was created with two independent modules: (a) the optimization procedure and (b) the numerical model of the motor. The optimization procedure used was a metaheuristic optimization method based on the gray wolf algorithm. Four design variables linked to the rotor structure were selected. The optimization process was performed from the rotor of a low-power induction motor (IM). The prototype of the motor (LSPMSM) was then built. The experimental measurements were performed for base the IM and optimized LSPMSM. The results of the measurements were compared for both motors. The experimental results confirmed the better performance of the designed motor in comparison to the induction motor.

show abstract

Section: Formulation Of the Design Problemmentioning

confidence: 99%

Optimization of Low-Power Line-Start PM Motor Using Gray Wolf Metaheuristic Algorithm

Knypiński

Pawełoszek

Menach³

2020

Energies

View full text Add to dashboard Cite

show abstract

“… In any case, it cannot reach the maximum level of the machine timing. [43] have discussed the mathematical model of the industrial programming problem as follows: (related to the Band saw of a product)…”

Section: Model Formulationmentioning

confidence: 99%

Interval-valued Trapezoidal Neutrosophic and Multi-Choice Parameters for Multi-objective Production Planning Problem

Haq,

Khan,

Ahmed

2024

Preprint

View full text Add to dashboard Cite

An intuitionistic multi-objective programming problem with interval-valued trapezoidal neutrosophic (IVTN) and multi-choice interval type has been considered in this paper. The coefficients of objective functions and parameters of the left side of the constraints are in the multi-choice environment, and the right-hand side of the constraints are in IVTN number type. The formulated problem’s multi-choice parameters were transformed into the deterministic form using the binary variable transformation technique. A procedure is defined to change the IVTN number into the deterministic form. Then, intuitionistic fuzzy programming with two different scalarization models has been used to achieve each membership goal’s highest degree and obtain a satisfactory decision-making solution. Finally, a numerical case study for production planning is explored to validate the work’s efficiency and usefulness.

show abstract

“…The compromise solution obtained by FP. Kamal et al (2019) described a bi-level multi-objective production planning problem in which some of the coefficients of objective functions and parameters of constraints are multi-choice. The multi-choices parameters of the prob-lem transformed into their equivalent deterministic form based on the binary variables.…”

Section: Literature Reviewmentioning

confidence: 99%

Multi-Objective Transportation Problem Under Type-2 Trapezoidal Fuzzy Numbers With Parameters Estimation and Goodness of Fit

et al. 2021

View full text Add to dashboard Cite

The problem of transportation in real-life is an uncertain multi-objective decision-making problem. In particular, by taking into account the conflicting objectives, Decision-Makers (DMs) are looking for the best transport set up to determine the optimum shipping quantity subject to certain capacity constraints on each route. This paper presented a Multi-Objective Transportation Problem (MOTP) where the objective functions are considered as Type-2 trapezoidal fuzzy numbers (T2TpFN), respectively. Demand and supply in constraints are in multi-choice and probabilistic random variables, respectively. Also considered the “rate of increment in Transportation Cost (TC) and rate of decrement in profit on transporting the products from ith sources to jth destinations due to” (or additional cost) of each product due to the damage, late deliveries, weather conditions, and any other issues. Due to the presence of all these uncertainties, it is not possible to obtain the optimum solution directly, so first, we need to convert all these uncertainties from the model into a crisp equivalent form. The two-phase defuzzification technique is used to transform T2TpFN into a crisp equivalent form. Multi-choice and probabilistic random variables are transformed into an equivalent value using Stochastic Programming (SP) approach and the binary variable, respectively. It is assumed that the supply and demand parameter follows various types of probabilistic distributions like Weibull, Extreme value, Cauchy and Pareto, Normal distribution, respectively. The unknown parameters of probabilistic distributions estimated using the maximum likelihood estimation method at the defined probability level. The best fit of the probability distributions is determined using the Akaike Information Criterion (AIC) and the Bayesian Information Criterion (BIC), respectively. Using the Fuzzy Goal Programming (FGP) method, the final problem is solved for the optimal decision. A case study is intended to provide the effectiveness of the proposed work.

show abstract

Bi-Level Multi-Objective Production Planning Problem with Multi-Choice Parameters: A Fuzzy Goal Programming Algorithm

Cited by 12 publications

References 44 publications

Optimization of Low-Power Line-Start PM Motor Using Gray Wolf Metaheuristic Algorithm

Optimization of Low-Power Line-Start PM Motor Using Gray Wolf Metaheuristic Algorithm

Interval-valued Trapezoidal Neutrosophic and Multi-Choice Parameters for Multi-objective Production Planning Problem

Multi-Objective Transportation Problem Under Type-2 Trapezoidal Fuzzy Numbers With Parameters Estimation and Goodness of Fit

Contact Info

Product

Resources

About