This article investigates a JIT single machine scheduling problem with a periodic preventive maintenance. Also to maintain the quality of the products, there is a limitation on the maximum number of allowable jobs in each period. The proposed bi-objective mixed integer model minimizes total earliness-tardiness and makespan simultaneously. Due to the computational complexity of the problem, mult...

Ecological sustainability has become a top priority for governments and business practitioners because of the massive surge in electronic waste (e-waste). This ecological context compelled firms to adopt reverse logistics (RL) invest advanced technologies with focus on sustainable recovery practices reducing excessive carbon emissions (CEs). study proposes multi-objective mixed integer programm...

Constrained optimization is a computationally difficult task, particularly if the constraint functions are non-linear and nonconvex. As a generic classical approach, the penalty function approach is a popular methodology which degrades the objective function value by adding a penalty proportional to the constraint violation. However, the penalty function approach has been criticized for its sen...

The paper is devoted to modeling wireless mesh networks (WMN) through mixed-integer programming (MIP) formulations that allow to precisely characterize the link data rate capacity and transmission scheduling using the notion of time slots. Such MIP models are formulated for several cases of the modulation and coding schemes (MCS) assignment. We present a general way of solving the max-min fairn...

State-of-the-art solvers for mixed integer programming (MIP) problems are highly parameterized, and finding parameter settings that achieve high performance for specific types of MIP instances is challenging. We study the application of an automated algorithm configuration procedure to different MIP solvers, instance types and optimization objectives. We show that this fully-automated process y...

Heuristics and metaheuristics are inevitable ingredients of most of the general purpose ILP solvers today, because of their contribution to the significant boost of the performance of exact methods. In the field of bi/multi-objective optimization, to the best of our knowledge, it is still not very common to integrate ILP heuristics into exact solution frameworks. This paper aims to bring a stro...