Tootfinder

Optimizing Fairness in Production Planning: A Human-Centric Approach to Machine and Workforce Allocation
Alexander Nasuta, Alessandro Cisi, Sylwia Olbrych, Gustavo Vieira, Rui Fernandes, Lucas Paletta, Marlene Mayr, Rishyank Chevuri, Robert Woitsch, Hans Aoyang Zhou, Anas Abdelrazeq, Robert H. Schmitt
https://arxiv.org/abs/2510.01094

Optimizing Fairness in Production Planning: A Human-Centric Approach to Machine and Workforce Allocation
This work presents a two-layer, human-centric production planning framework designed to optimize both operational efficiency and workforce fairness in industrial manufacturing. The first layer formulates the Order-Line allocation as a Constraint Programming (CP) problem, generating high-utilization production schedules that respect machine capacities, processing times, and due dates. The second layer models Worker-Line allocation as a Markov Decision Process (MDP), integrating human factors suc…

Efficient Approximation Algorithms for Fair Influence Maximization under Maximin Constraint
Xiaobin Rui, Zhixiao Wang, Chen Peng, Qiangpeng Fang, Wei Chen
https://arxiv.org/abs/2509.26579

Efficient Approximation Algorithms for Fair Influence Maximization under Maximin Constraint
Aiming to reduce disparities of influence across different groups, Fair Influence Maximization (FIM) has recently garnered widespread attention. The maximin constraint, a common notion of fairness adopted in the FIM problem, imposes a direct and intuitive requirement that asks the utility (influenced ratio within a group) of the worst-off group should be maximized. Although the objective of FIM under maximin constraint is conceptually straightforward, the development of efficient algorithms wit…

Optimizing Fairness in Production Planning: A Human-Centric Approach to Machine and Workforce Allocation
Alexander Nasuta, Alessandro Cisi, Sylwia Olbrych, Gustavo Vieira, Rui Fernandes, Lucas Paletta, Marlene Mayr, Rishyank Chevuri, Robert Woitsch, Hans Aoyang Zhou, Anas Abdelrazeq, Robert H. Schmitt
https://arxiv.org/abs/2510.01094

Optimizing Fairness in Production Planning: A Human-Centric Approach to Machine and Workforce Allocation
This work presents a two-layer, human-centric production planning framework designed to optimize both operational efficiency and workforce fairness in industrial manufacturing. The first layer formulates the Order-Line allocation as a Constraint Programming (CP) problem, generating high-utilization production schedules that respect machine capacities, processing times, and due dates. The second layer models Worker-Line allocation as a Markov Decision Process (MDP), integrating human factors suc…