A multi-product mathematical model for iron ore stockyard planning problem

Abstract

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

A Linear Relaxation-Based Heuristic for Iron Ore Stockyard Energy Planning

“…From this analysis and considering MILP mathematical model ( 1)-( 10) and the LP mathematical model (deleting (11) and adding ( 13)), the information contained in Tables 4 and 5 was used to create the various instances. For this purpose, that, we wrote a code in the Python programming language to generate the input data, and we wrote the model in an adequate format for the CPLEX [9] to perform the optimization of each of the scenarios, using the standard settings of this solver. This code in the Python language applies the library package CPLEX to run the LP and MILP and also to facilitate the procedures of the LRBH that use the CPLEX and its functions as part of the code.…”

“…Lastly, the work in [9] presented a bi-objective MILP model to determine the ships that will be served by each berth in a given queue of customers. The authors used objective functions separately and evaluated their behavior in the studied instances.…”

“…In the same way as in Table 1, this problem is summarized in Table 3. The verification and validation procedures for the model proposed in this study were performed with the aid of the commercial solver-CPLEX 12.5 [9]. Random values were used to define the demand of each ship and create simulated instances using parameters based on those in [9,24].…”

“…and waste in the production process. Due to the full range of production scheduling problems, there are several approaches for stockyard planning, including manual computer-supported programming (such as interactive Gantt charts), expert systems, mathematical programming, heuristics, evolutionary algorithms, and different artificial intelligence methods (e.g., [2][3][4][5][6][7][8][9]). The optimal solution will result in significant savings through better capacity utilization.…”

“…In real situations, the equipment or participants must be considered, such as the flows between the machines, the amount of cargo loaded on the ships, and the number of ships served, thereby increasing the complexity. Planning a stockyard-port system considering a variety of products is made more complicated by the emergence of new flows and variables that measure the equipment or changes in their characteristics [9].…”