Code Design as an Optimization Problem: from Mixed Integer Programming to an Improved High Performance Randomized GRASP like Algorithm and from This One to an Improved Genetic Algorithm

2006 ◽  
Author(s):  
Jose Da Fonseca
Keyword(s):  
Genetic Algorithm ◽  
Integer Programming ◽  
Mixed Integer Programming ◽  
High Performance ◽  
Optimization Problem ◽  
Mixed Integer ◽  
Code Design ◽  
Improved Genetic Algorithm

GA-CDFM Based Hybrid Optimization Method for Steelmaking Scheduling and Caster Operation

2012 ◽  
Vol 424-425 ◽  
pp. 994-998 ◽  
Author(s):  
Xiao Chuan Luo ◽  
Chong Zheng Na
Keyword(s):  
Genetic Algorithm ◽  
Integer Programming ◽  
Mixed Integer Programming ◽  
Programming Model ◽  
Optimization Method ◽  
Optimal Performance ◽  
Hybrid Optimization ◽  
Mixed Integer ◽  
Algorithm Optimization ◽  
Genetic Algorithm Optimization

In steelmaking plant, the process times of machines change frequently and randomly for the reason of metallurgical principle. When those change happen, the plant scheduling and caster operation must respond to keep the optimal performance profile of plant. Therefore, the integration of plant scheduling and caster operation is a crucial task. This paper presents a mixed-integer programming model and a hybrid optimized algorithm for caster operation and plant scheduling, which combine the genetic algorithm optimization and CDFM process status verification. Data experiments illustrate the efficiency of our model and algorithm.

Grade control in multi-variable ore deposits as a quality management problem under uncertainty

2015 ◽  
Vol 32 (4) ◽  
pp. 334-345 ◽  
Author(s):  
Mustafa Kumral
Keyword(s):  
Quality Control ◽  
Integer Programming ◽  
Control Problem ◽  
Mixed Integer Programming ◽  
Optimization Problem ◽  
Mixed Integer ◽  
Mining Operations ◽  
Content Type ◽  
Non Linear ◽  
Grade Control

Purpose – The purpose of this paper is to provide a decision-making tool on where to send mining parcels extracted in such a way as to minimize losses arising from mis-classification. The problem is complicated because actual values of mining parcels cannot be known and the decision is made on the basis of the estimation/simulations of the parcels generated from sparse data. Design/methodology/approach – The loss minimization associated with mis-classification is formulated as a non-linear optimization problem and solved by successive mixed integer programming. By assigning reasonable values to some variables making problem non-linear, the problem is converted to a mixed integer programming (MIP) and is solved by a standard MIP optimization engine. Findings – A case study was conducted to see the performance of the proposed approach on a deposit with gold and silver variables. The proposed approach was also compared with conventional grade control approaches. The results showed that the approach proposed could be used for solving grade quality control problem. Practical implications – Grade quality control problem is well-known problem and there is no effective solution approach. This paper proposes to solve the problem through standard operation research software. As such, mine planner and engineers have a means to deal with grade quality problem in mining operations. Originality/value – The paper formulates multi-variable grade quality control problem as an optimization problem on the contrary to previous one-shot approaches. This can increase profit and operation efficiency. The research also use target grades rather than cut-off grade posing problems in mining operations.

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