A Multi-Worker Assembly Line Rebalancing with Spatial and Ergonomic Considerations

Martina Vinetti, Sabino Franceso Roselli, and Martin Fabian.

This is the official repository for A Multi-Worker Assembly Line Rebalancing with Spatial and Ergonomic Considerations.
It contains the Python implementations of the proposed linear and quadratic ALRBP models, the procedures to generate feasible incumbent solutions, and the scripts required to reproduce all experimental results reported in the paper.

Abstract

This work addresses the Assembly Line Rebalancing Problem in manual assembly systems where multiple workers operate in parallel within the same station—an industrially relevant scenario that remains insufficiently explored in the literature. A multi-objective optimization model is proposed that incorporates task reassignment, worker allocation, ergonomic evaluation, and explicit spatial feasibility through work-area constraints. The formulation minimizes deviations from the current configuration while promoting balanced workload and ergonomic conditions among workers.

Computational experiments on synthetic problem instances demonstrate that the model consistently generates feasible and human-centered reconfigurations across varying cycle-time conditions, highlighting its potential as a decision-support tool for industrial rebalancing in flexible production environments.

Repository Structure

ALRBP/
├── README.md                        # Project overview + steps to reproduce experiments
├── requirements.txt                 # Python dependencies (incl. gurobipy)
├── LICENSE                          # License information
│
├── data/
│   ├── synthetic_instances/         # Randomly generated (potentially infeasible) instances
│   │
│   ├── feasible_instances/
│   │   ├── opt/                     # Feasible incumbents from ALBP solved to optimality
│   │   └── subopt/                  # Feasible incumbents from ALBP with target MIPGap (e.g., 80%)
│   │
│   └── norm_values/                 # Nadir/utopia (or normalization) values used to scale objectives
│
└── src/
    ├── models/
    │   ├── Q_ALRBP_model.py              # Rebalancing model (quadratic area constraint)
    │   └── L_ALRBP_model.py              # Rebalancing model (linearized area constraint)
    │
    └── scripts/
        ├── run_ALBP.py                   # Runs ALBP on synthetic instances -> feasible_instances/(opt|subopt)
        ├── norm_values.py                # Computes normalization values -> data/norm_values/
        └──  run_ALRBP.py                 # Runs ALRBP (both quadratic and linear) on feasible instances   

Getting Started

Prerequisites

1. Python (version 3.11 or higher)
2. Install required dependencies using:

pip install -r requirements.txt

3. Solver:
   • Gurobi Optimizer

Running the Code

run_ALRBP.py – loads feasible instances and solves the Assembly Line Rebalancing Problem using either the linear or quadratic formulation.

Licence

This project is licensed under the MIT License. See LICENSE for details.