Planning the use of electrical energy in a bulk stockyard is a strategic issue due to its impact on efficiency and responsiveness of these systems. Empirical planning becomes more complex when the energy cost changes over time. The mathematical models currently studied in the literature consider many actors involved, such as equipment, sources, blends, and flows. Each paper presents different combinations of actors, creating their own transportation flows, thus increasing the complexity of this problem. In this work, we propose a new mixed integer linear programming (MILP) model for stockyard planning solved by a linear relaxation-based heuristic (LRBH) to minimize the plan’s energy cost. The proposed algorithm will allow the planner to find a solution that saves energy costs with an efficient process. The numerical results show a comparison between the exact and heuristic solutions for some different instances sizes. The linear relaxation approach can provide feasible solutions with a 3.99% average distance of the objective function in relation to the optimal solution (GAP) in the tested instances and with an affordable computation time in instances where the MILP was not able to provide a solution. The model is feasible for small and medium-sized instances, and the heuristic proposes a solution to larger problems to aid in management decision making.

Stockyard–port planning is a complex combinatorial problem that has been studied primarily through simulation or optimization techniques. However, due to its classification as non-deterministic polynomial-time hard (NP-hard), the generation of optimal or near-optimal solutions in real time requires optimization techniques based on heuristics or metaheuristics. This paper proposes a deterministic simulation and a meta-heuristic algorithm to address the stockyard–port planning problem, with the aim of reducing the time that ships spend in berths. The proposed algorithm is based on the ore handling operations in a real stockyard–port terminal, considering the interaction of large physical equipment and information about the production processes. The stockyard–port system is represented by a graph in order to define ship priorities for planning and generation of an initial solution through a deterministic simulation. Subsequently, the Variable Neighborhood Descent (VND) meta-heuristic is used to improve the initial solution. The convergence time of VND ranged from 1 to 190 s, with the total number of ships served in the berths varying from 10 to 1000 units, and the number of stockyards and berths varying from 11 to 15 and 3 to 5, respectively. Simulation results demonstrate the efficiency of the proposed algorithm in determining the best allocation of stockpiles, berths, car-dumpers, and conveyor belts. The results also show that increasing the number of conveyor belts is an important strategy that decreases environmental impacts due to exposure of the raw material to the atmosphere, while also increasing the stockyard–port productivity. This positive impact is greater when the number yards and ship berths increases. The proposed algorithm enables real-time decision-making from small and large instances, and its implementation in an iron ore stockyard–port that uses Industry 4.0 principles is suitable.

O aumento da geração de resíduos faz com que seja necessária a implantação de uma série de ações para evitar os problemas ambientais, sendo essa uma responsabilidade compartilhada de toda a sociedade. Logo, o presente artigo tem como objetivo indicar através do método do centro de gravidade a melhor localização de um ponto de coleta de óleo de cozinha no município de Vitória, evidenciando a aplicabilidade do método escolhido para definir a localização. A partir da metodologia escolhida foi realizada uma revisão de literatura na qual se divide em dois temas, gestão de resíduos e aplicação do método do centro de gravidade, contribuindo para a contextualização do tema da pesquisa destacando a relevância do mesmo. Entretanto, considerando o método escolhido foram listados os 80 bairros do município, bem como as coordenadas geográficas dos mesmos. Além disso, foram utilizadas as demandas de consumo em cada bairro nos cenários de 5 e 15 anos. No entanto, a partir da técnica escolhida foi possível observar que a localização proposta está entre os bairros com o maior consumo de óleo de cozinha.

A multi-product mathematical model for iron ore stockyard planning problem / Um modelo matemático multiprodutos para o problema de planejamento de meios de ferro

Designing a supply chain is a major strategic issue due to its impact on efficiency and responsiveness. The design becomes more complex when the goal is to reduce distribution costs and use the time postponement in the supply chain. The mathematical models currently studied in the literature consider various actors involved in the network. However, in real problems there are different combinations of actors, creating own transportation flows and increasing the complexity of a supply chain. This paper proposes a model for designing supply chains with time postponement from a mixed integer non-linear programming formulation to minimize the total costs, considering the transportation, facilities opening and operational costs. The model allows the possibility of a hybrid facility, that is, two kinds of facilities opened in the same place, an important opportunity to saving costs. Some sets of instances were simulated to find the optimal solution of that model and analyze the supply chain behavior in different instances sizes. These scenarios were solved by a commercial solver and its performance was assessed. The model presents feasibility of use for small and medium-sized instances with enough computing time to aid in management decision making.