Hybrid Multi-objective Optimization Method for Solving Simultaneously the line Balancing, Equipment and Buffer Sizing Problems for Hybrid Assembly Systems

Oesterle, Jonathan; Bauernhansl, Thomas; Yalaoui, Farouk

doi:10.1016/j.procir.2016.11.072

Cited by 8 publications

(3 citation statements)

References 30 publications

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“…Later, [34] proposed a multi-objective mathematical formulation and a hybrid genetic algorithm to solve buffer sizing and machine allocation problems simultaneously for throughput maximization and total cost minimization. A hybrid multi-objective optimization algorithm based on an adaptation of the Pareto hill climbing and NSGA-II was proposed in [35]. Authors studied the line balancing, equipment selection, and buffer sizing problem for idle time and total unit costs minimization as well as throughput maximization.…”

Section: B the Multi-objective Bapmentioning

confidence: 99%

“…Although the literature related to multi-objective optimization algorithms is very rich with various evolutionarybased algorithms having interesting search and convergence performances, most recent multi-objective studies of the BAP use either the NSGA-II [39] or hybrid approaches combining NSGA-II with other evolutionary algorithms such as [35], [36], [38]. Although the developed hybrid algorithm TS-NSGA-II in [36] demonstrated good performance, the NSGA-II still shows equivalent overall performance with a better breadth of search and less computational time than the developed hybrid approach.…”

Section: B the Multi-objective Bapmentioning

confidence: 99%

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Multi-Objective Optimization of Energy-Efficient Buffer Allocation Problem for Non-Homogeneous Unreliable Production Lines

2022

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The current context of rising ecological awareness and high competitiveness, reveals a strong necessity to integrate the sustainability paradigm into the design of production systems. The buffer allocation problem is of particular interest since buffers absorb disruptions in the production line. However, despite the rich literature addressing the BAP, there are no studies that use a multi-objective framework to deal with energetic considerations. In this study, the energy-efficient buffer allocation problem (EE-BAP) is studied through a multi-objective resolution approach. The multi-objective problem is solved to optimize two conflicting objectives: maximizing production throughput and minimizing its energy consumption, under a total storage capacity available. The weighted sum and epsilon-constraint methods as well as the elitist non-dominated sorting genetic algorithm (NSGA-II) are adapted and implemented to solve the EE-BAP. The obtained solutions are analyzed and compared using different performance metrics. Numerical experiments show that epsilon-constraint outperforms the NSGA-II when considering comparable computational time. The Pareto solutions obtained are trade-offs between the two objectives, enabling decision making that balances productivity maximization with energy economics in the design of production lines.

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Section: B the Multi-objective Bapmentioning

confidence: 99%

Section: B the Multi-objective Bapmentioning

confidence: 99%

Multi-Objective Optimization of Energy-Efficient Buffer Allocation Problem for Non-Homogeneous Unreliable Production Lines

2022

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“…This study based on case study that is ultimately discussed to demonstrate the capabilities of the proposed method in finding the optimal solution [1] . Another research on line balancing suggests that multi-objective hybrid optimization algorithms aimed at simultaneously resolving line balancing, equipment and buffer selection, measuring problems with capacity-oriented capacity and objectives, in other words looking to optimize in the production path [2] Research for line balancing is widely applied to the manufacturing industry as in research conducted on the world of airplanes [3]. In other hand, there was also a line balancing study conducted in the automotive industry such as done in the europe automotive industry [4].…”

Section: Introductionmentioning

confidence: 99%

The Balance Improvement of Final Assembly Water Pump Business Unit Tracks Section : Case Study

et al. 2017

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Abstract. This research was conducted at an electronic field assembly company. The company implements a production system that starts from semi-finished goods to finished products. The problem of the company is the imbalance of the production trajectory. The track balance in the final assembly will affect the amount of product that can be produced. The unbalanced track conditions resulted a bottleneck condition in the material flow from one work center to the other, resulting in delay time on the production floor. The problems are caused by large cycle times, thus resulting in different production capacities for each workcenter. The implementation of the theory of constraints is to identify the existing constraints and to obtain the optimum amount of workcenter as well as to allocate elements of activity in the workcenter, thereby improving the efficiency of the production line.. In actual trajectory there are 7 work centers with track path efficiency 59,80%, balance delay 40,20%, and smoothing index 74,47. The result of balancing in the production line using theory of constraint method obtained the repair solution by number of work center as many as 5 work centers with track efficiency value 88,65%, balance delay 11,35% and smoothing index 17,07.

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A multi-objective hybrid evolutionary approach for buffer allocation in open serial production lines

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2018

J Intell Manuf

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Hybrid Multi-objective Optimization Method for Solving Simultaneously the line Balancing, Equipment and Buffer Sizing Problems for Hybrid Assembly Systems

Cited by 8 publications

References 30 publications

Multi-Objective Optimization of Energy-Efficient Buffer Allocation Problem for Non-Homogeneous Unreliable Production Lines

Multi-Objective Optimization of Energy-Efficient Buffer Allocation Problem for Non-Homogeneous Unreliable Production Lines

The Balance Improvement of Final Assembly Water Pump Business Unit Tracks Section : Case Study

A multi-objective hybrid evolutionary approach for buffer allocation in open serial production lines

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