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

Yasmine Alaouchiche,Farouk Yalaoui,Yassine Ouazene

doi:10.1109/access.2021.3139954

Yasmine Alaouchiche, Farouk Yalaoui + Show 1 more

Open Access

https://doi.org/10.1109/access.2021.3139954

Copy DOI

Journal: IEEE Access	Publication Date: Jan 1, 2022
Citations: 6	License type: CC BY 4.0

Affiliation: University of Technology of Troyes

Abstract

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.

Highlights

The buffer allocation problem (BAP) is a design problem in production systems that aims to find the optimal allocation of storage space to achieve system efficiency
The dual BAP focuses on throughput maximization with a total buffer capacity as a constraint
This paper presented a study on the multi-objective EEBAP

Summary

INTRODUCTION

The buffer allocation problem (BAP) is a design problem in production systems that aims to find the optimal allocation of storage space to achieve system efficiency. In [33], a genetic algorithm combined to line search method was used to solve the multi-objective model for throughput and buffer size optimization. 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. As stated in the literature review section, the objectives to optimize are in most cases the equivalent throughput of the system (to be maximized) and the total buffer space allocated (to be minimized), either in a single or a multi-objective optimization procedure. If the production line involves 10 machines with a total buffer capacity of 100, the total number of feasible buffer allocations becomes 3.52 × 1011 This indicates the computational difficulty to search through the whole solution space by complete enumeration even for small sized problems.

TEST RESULTS

PERFORMANCE COMPARATIVE STUDY

Findings

CONCLUSION