A Water-Flow Like Algorithm for Solving U-Shaped Assembly Line Balancing Problems

Nourmohammadi, Amir; Fathi, Masood; Zandieh, M.; Ghobakhloo, Morteza

doi:10.1109/access.2019.2939724

Cited by 21 publications

(19 citation statements)

References 33 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…In the WFA, water-flows and terrains are considered as solutions and search space, respectively. The WFA operates based on several procedures ( Yang and Wang, 2007 , Nourmohammadi et al, 2019 ): (1) Splitting and moving procedures, (2) Merging, (3) Evaporation, and (4) Precipitation. In order to save space, the procedures of the classical WFA have been explained in Appendix A.…”

Section: Solution Methodologymentioning

confidence: 99%

“…The classical WFA method uses the following procedures to solve an optimization problem. These procedures continue until a termination condition is reached ( Yang and Wang, 2007 , Nourmohammadi et al, 2019 ): Splitting and moving procedures: As the water-flows pass the terrains, they are divided into multiple sub-flows. Then, they tend to flow through lower terrains.…”

Section: Procedures Of the Classical Wfamentioning

confidence: 99%

“…The number of sub-flows derived from the flow F is obtained by Eq. (69) ( Yang and Wang, 2007 , Nourmohammadi et al, 2019 ):…”

Section: Procedures Of the Classical Wfamentioning

confidence: 99%

“…The mass and the velocity of each sub-flow are calculated by Eqs. (70) , (71) , respectively ( Yang and Wang, 2007 , Nourmohammadi et al, 2019 ):

…”

Section: Procedures Of the Classical Wfamentioning

confidence: 99%

See 3 more Smart Citations

A healthcare logistic network considering stochastic emission of contamination: Bi-objective model and solution algorithm

Nikzamir

Baradaran

2020

Transportation Research Part E: Logistics and Transportation Re

View full text Add to dashboard Cite

Highlights A novel healthcare waste location-routing problem is developed with a new perspective in healthcare logistics networks. A stochastic essence for the emission of contamination is considered. The management of medical wastes in Coronavirus Disease 2019 is focused. A real case study is modeled to manage the logistics of infectious and non-infectious healthcare wastes. A Multi-Objective Water-Flow like Algorithm with novel operators is developed and compared with the others.

show abstract

Section: Solution Methodologymentioning

confidence: 99%

Section: Procedures Of the Classical Wfamentioning

confidence: 99%

“…The number of sub-flows derived from the flow F is obtained by Eq. (69) ( Yang and Wang, 2007 , Nourmohammadi et al, 2019 ):…”

Section: Procedures Of the Classical Wfamentioning

confidence: 99%

“…The mass and the velocity of each sub-flow are calculated by Eqs. (70) , (71) , respectively ( Yang and Wang, 2007 , Nourmohammadi et al, 2019 ):

…”

Section: Procedures Of the Classical Wfamentioning

confidence: 99%

See 2 more Smart Citations

A healthcare logistic network considering stochastic emission of contamination: Bi-objective model and solution algorithm

Nikzamir

Baradaran

2020

Transportation Research Part E: Logistics and Transportation Re

View full text Add to dashboard Cite

show abstract

“…In this experiment, the validation process included the throughput for the different variants of products being produced in every one of the four assembly lines. These validated models allow for system analysis such as identifying bottlenecks, balance problems, and shape distributions on the facility layout [35][36][37][38][39]. When these problems become NPhard, approximation methods approaches are recommended.…”

Section: Developmentmentioning

confidence: 99%

A Simulation-Based Optimization Methodology for Facility Layout Design in Manufacturing

et al. 2020

Self Cite

View full text Add to dashboard Cite

Optimizing production systems is urgent and indispensable if companies are to cope with global competition and a move from mass production to mass customization. The urgency of this need is more obvious in old production plants with a history of modifications, expansions, and adaptations in their production facilities. It is common to find complex, intricate and inefficient systems of material and product flows as a result of poor production facility layout. Several approaches can be used to support the design of optimal facility layouts. However, there is a lack of a suitable generic methodology for designing such layouts. Additionally, there has been little focus on the data and resources required, or on how simulation and optimization can support the design of optimal facilities. To overcome these deficiencies, this paper studies the integration of simulation and optimization for the design and improvement of facility layouts taking into account production and logistics constraints. The paper includes a generic perspective and a detailed implementation. The proposed methodology is evaluated in two case studies and by drawing on the principles and tools of the functional resonance analysis method. This method analyzes the implementation order and variability of a group of processes that can lead to unwanted outcomes. The results can provide managers and other stakeholders with a methodology that adequately considers production and logistics constraints when seeking an optimized facility layout design.

show abstract

Energy‐efficient and sustainable supply chain in the manufacturing industry

Beheshtinia

Fathi

2022

Energy Science & Engineering

Self Cite

View full text Add to dashboard Cite

This study aims at reducing energy consumption in supply chain networks by providing optimal integrated production and transportation scheduling. The considered supply chain consists of one main manufacturing center, multiple production units (i.e., suppliers), and multiple heterogeneous vehicles as the transportation fleet. To schedule this complex supply chain network in an energy-efficient way, several decisions should be made concerning the assignment of orders to suppliers and determining their production sequence, splitting orders, assigning orders to vehicles, and assigning delivery priority to orders. To cope with the problem, a mixed-integer linear programming model is presented. Due to the complexity of the problem, a novel development of the genetic algorithm named the Multiple Reference Group Genetic Algorithm (MRGGA) is also proposed. Four objectives are considered to be optimized to meet both suitability and energy-efficiency aspects in the supply chain network. These optimization objectives are to minimize the total orders' delivery times to the manufacturing center, fuel consumption by the vehicles, energy consumption at supplies, and maximize orders' quality. To analyze the performance of the proposed algorithm, a real case and a set of generated instances are solved. The results obtained by the proposed algorithm are compared with an existing genetic algorithm in the literature. Moreover, the results are also compared with the optimal solutions obtained from the mathematical model for small-size problems. The results of the comparisons show the efficiency of the proposed MRGGA in finding energy-efficient solutions for the considered supply chain network.

show abstract

A Water-Flow Like Algorithm for Solving U-Shaped Assembly Line Balancing Problems

Cited by 21 publications

References 33 publications

A healthcare logistic network considering stochastic emission of contamination: Bi-objective model and solution algorithm

A healthcare logistic network considering stochastic emission of contamination: Bi-objective model and solution algorithm

A Simulation-Based Optimization Methodology for Facility Layout Design in Manufacturing

Energy‐efficient and sustainable supply chain in the manufacturing industry

Contact Info

Product

Resources

About