Research On Modeling And Optimization For Bulk Cargo Logistics Planning And Scheduling In Steel Industry

Raw materials such as iron ore and coal play an essential role in steel production,which consumes high resources and energy.How to scientifically determine the logistics planning of inventory and transportation as well as the logistics operations scheduling of raw materials unloading,handling,stacking and retrieving is not only essential practical problem for the industry,but also significant technical challenge for the academia.This paper investigates the modeling and optimization methods for raw material logistics planning and scheduling problems arising from the practice,to help steel enterprises promote the operation efficiency,reduce the costs.First,a discrete modeling method for the planning and scheduling problems with no-interruption operation structure is developed,and then applied to the modeling of the quay crane scheduling problem,the integrated storage space allocation and ship scheduling problem,and the integrated reclaimer and belt conveyor scheduling problem.Second,Benders decomposition algorithms are developed to solve these problems.At last,the raw material distribution network design problem is addressed,and then solved by Benders decomposition algorithm.1)For the quay crane scheduling problem,to handle the case that Benders,work poorly for existing models,this paper proposes a new master-slave modeling techique to establish the models of Benders master problem and sup-problem,respectively.The master problem is established for the task-assignment decisions through defining new variables and constraints of group assignment and inter-group assignment,while the sub-problem is to determine the operation sequence.Several accelerating strategies is developed and embedded into the proposed approach,such as valid inequality,splitted sub-problems,and logic-based Benders cut.Computational experiments are conducted to evaluate the performance of the proposed approach.(2)For the integrated storage space allocation and ship scheduling problem,which is different from other associated problems due to the special way that the materials are transported and stored,an innovative mixed-integer programming model(MILP)is developed,and then solved by a Benders decomposition algorithm,which is enhanced by the use of various valid inequalities,combinatorial Benders cuts and variable reduction tests.Computational results indicate that the proposed solution method is much more efficient than the standard solution software CPLEX.(3)For the reclaimer and belt-conveyor scheduling problem,which suffers from the computational complexity arising from the interdependence and interference between various items of associated transport equipment such as reclaimers and belt conveyors,the paper established a discrete-time based mixed integer programming model to minimize the finishing time of handling tasks assigned by each production facility.Furthermore,based on the status nodes and flows proposed in the paper,a novel time-space network flow model is established to solve the problem more efficiently.In order to gain a meaningful alignment,a traditional continuous-time scheduling model is also given.Computational studies are performed to show the effectiveness of our proposed models.(4)For the distribution system network design problem,new distribution structure is considered that some retailers can be selected as the second-stage distribution center,and that the truckload capacity need to be installed for each transportation link.A mixed integer programming model is established to minimizing the total distribution-center construction cost,the truck-load-installation cost and transportation cost,and then solved by Benders algorithm,which is enhanced by the strengthened Benders cut strategy.Computational experiments are conducted to evaluate the performance of the proposed algorithm.