scholarly journals Integrated Scheduling for Steelmaking Continuous Casting— Hot Rolling Processes considering Hot Chain Logistics

2020 ◽  
Vol 2020 ◽  
pp. 1-10
Author(s):  
Sen Wang ◽  
Yarong Shi ◽  
Shixin Liu
Keyword(s):  
Continuous Casting ◽  
Energy Saving ◽  
Hot Rolling ◽  
Production Scheduling ◽  
Programming Model ◽  
Mathematical Programming Model ◽  
Integrated Scheduling ◽  
Temperature Loss ◽  
Slab Temperature ◽  
Consumption Energy

Steelmaking continuous casting (SCC)—hot rolling (HR) is a key process in the production of steel products. It is also a process with large energy consumption. Energy saving has always been an important goal of production scheduling of this process. In this paper, aiming at integrated scheduling optimization for SCC-HR processes, energy saving objective is converted to minimize waiting time of slabs in slab yard, so as to reduce slab temperature loss and achieve the goal of saving energy. An integrated two-stage mathematical programming model is established for the above problems, and a hybrid algorithm of genetic algorithm and linear programming is designed for the integrated model. The correctness of the model and the validity of the algorithm are verified by computational experiments using simulated instances.

scholarly journals Mathematical Programming for Lot Sizing and Production Scheduling in Foundries

2014 ◽  
Vol 14 (3) ◽  
pp. 17-20 ◽  
Author(s):  
J. Duda ◽  
A. Stawowy ◽  
R. Basiura
Keyword(s):  
Mathematical Programming ◽  
Production Scheduling ◽  
Programming Model ◽  
Lot Sizing ◽  
Mathematical Programming Model ◽  
Rolling Horizon Planning ◽  
Horizon Planning ◽  
Number Of Customers ◽  
Lot Sizing And Scheduling ◽  
Melted Metal

Abstract The problem considered in the paper is motivated by production planning in a foundry equipped with the furnace and casting line, which provides a variety of castings in various grades of cast iron/steel for a large number of customers. The quantity of molten metal does not exceed the capacity of the furnace, the load is a particular type of metal from which the products are made. The goal is to create the order of the melted metal loads to prevent delays in delivery of goods to customers. This problem is generally considered as a lot-sizing and scheduling problem. The paper describes a mathematical programming model that formally defines the optimization problem and its relaxed version that is based on the conception of rolling-horizon planning.

scholarly journals Integrated Scheduling of Reheating Furnace and Hot Rolling Based on Improved Multiobjective Differential Evolution

Complexity ◽  
2018 ◽  
Vol 2018 ◽  
pp. 1-19 ◽  
Author(s):  
Kun Li ◽  
Huixin Tian
Keyword(s):  
Differential Evolution ◽  
Hot Rolling ◽  
Rolling Mill ◽  
Programming Model ◽  
Novel Mutation ◽  
Mixed Integer ◽  
Scheduling Problems ◽  
Reheating Furnace ◽  
Integrated Scheduling ◽  
Hot Rolling Mill

In the hot rolling mill, a cold slab is reheated in reheating furnace and then rolled into thin coils through hot rolling process. Traditional research on hot rolling mill generally takes the two processes as two separate single-objective scheduling problems, though they are closely connected and their optimization objectives are conflicting with each other. In this paper, the integrated scheduling of the reheating furnace and hot rolling is investigated in the view of multiobjective optimization. A mixed-integer programming model with two objectives is formulated for this problem, and a multiobjective differential evolution (MODE) algorithm is developed to solve this model. To make it easy for algorithm design, a hot rolling schedule (i.e., a sequence of slabs) is used to represent a solution and for a given solution, a heuristic with consideration of energy consumption minimization is presented to obtain the schedule of reheating furnace. To achieve the balance of exploration and exploitation, a novel mutation operator with adaptive leader selection, a crossover operator with feasibility consideration, and a guided multiobjective local search are designed. Computational results based on simulated data illustrate that the integrated scheduling is superior to the traditional two-phase scheduling method used in practice and literature. Further results illustrate that the proposed MODE algorithm is effective and superior to some other multiobjective evolutionary algorithms.

Scheduling a Bus Fleet for Evacuation Planning Using Stop-Skipping Method

2021 ◽  
pp. 036119812110200
Author(s):  
Hu Zhao ◽  
Shumin Feng ◽  
Yusheng Ci
Keyword(s):  
Waiting Time ◽  
Ant Colony Algorithm ◽  
Programming Model ◽  
Peer To Peer ◽  
Mathematical Programming Model ◽  
Fleet Size ◽  
Bus Stop ◽  
Passenger Demand ◽  
Service Strategies ◽  
Bus System

Sudden passenger demand at a bus stop can lead to numerous passengers gathering at the stop, which can affect bus system operation. Bus system operators often deal with this problem by adopting peer-to-peer service, where empty buses are added to the fleet and dispatched directly to the stop where passengers are gathered (PG-stop). However, with this strategy, passengers at the PG-stop have a long waiting time to board a bus. Thus, this paper proposes a novel mathematical programming model to reduce the passenger waiting time at a bus stop. A more complete stop-skipping model that including four cases for passengers’ waiting time at bus stops is proposed in this study. The stop-skipping decision and fleet size are modeled as a dynamic program to obtain the optimal strategy that minimizes the passenger waiting time, and the optimization model is solved with an improved ant colony algorithm. The proposed strategy was implemented on a bus line in Harbin, China. The results show that, during the evacuation, using the stop-skipping strategy not only reduced the total waiting time for passengers but also decreased the proportion of passengers with a long waiting time (>6 min) at the stops. Compared with the habitual and peer-to-peer service strategies, the total waiting time for passengers is reduced by 31% and 23%, respectively. Additionally, the proportion of passengers with longer waiting time dropped to 43.19% by adopting the stop-skipping strategy, compared with 72.68% with the habitual strategy and 47.5% with the peer-to-peer service strategy.

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