In this paper, a mixed-integer linearized programming (MINLP) model is presented to design a group layout (GL) of a cellular manufacturing system (CMS) in a dynamic environment and considering production planning (PP) decisions. This model incorporates an extensive coverage of important manufacturing features used in the design of CMSs. There are also some features that make the presented model...

Production planning and scheduling in the steel industry are challenging problems due to large number of products being produced. This work deals with scheduling of the continuous casting of steelmaking, i.e. determination of charge sequence in each casting machine. Since a full-space model Mixed-Integer Linear Programming (MILP) approach is computationally intractable for long term continuous ...

In this work we propose a simultaneous scheduling and control optimization formulation to address both optimal steady-state production and dynamic product transitions in multiproduct tubular reactors working in several parallel production lines. Because the problem involves integer and continuous variables and the dynamic behavior of the underlying system the resulting optimization problem is c...

This paper is a polyhedral study of a generalization of the mixing set where two different, divisible coefficients are allowed for the integral variables. Our results generalize earlier work on mixed integer rounding, mixing, and extensions. They also directly apply to applications such as production planning problems involving lower bounds or start-ups on production, when these are modeled as ...

Unequal reactive power sharing amongst distributed generators (DG) is a significant concern while operating droop based microgrid. The reasons for this unequal include the difference in feeder impedances, uneven distribution of loads and DGs terms size locations. In article, mixed-integer linear programming (MILP) problem applicable microgrid has been proposed to achieve proportional maintainin...

Abstract We study here systems of distributed entities that can actively modify their communication network. This gives rise to algorithms apart from also exploit network reconfiguration carry out a given task. Also, the task itself may now require global initial $$G_s$$ G s </mml:...

This study considers a real-world multi-period, multi-product production planning problem involving set-up constraints, with random yield and demand. The resulting large-scale multi-stage stochastic mixed-integer model cannot be solved by using the mixed-integer solver of a commercial optimization package. The production planning model is a mixed-integer programming (MIP) model without any spec...

Production planning is a necessary process that directly affects the efficiency of production systems in most industries. The complexity current problem depends on increased options production, uncertainties demand and resources. In this study, stochastic multi-objective mixed-integer optimization model developed to ensure uncertainty conditions satisfy requirements sustainable development. sys...

This paper presents a genetic algorithm (GA) for solving a generalized model of single-item resource-constrained aggregate production planning (APP) with linear cost functions. APP belongs to a class of pro-duction planning problems in which there is a single production variable representing the total production of all products. We linearize a linear mixed-integer model of APP subject to hiring...