A Differential Evolution Based Optimization Algorithm for Production Planning Model in Defense Industry

2013 ◽  
Vol 709 ◽  
pp. 249-252
Author(s):  
Yu Zhou ◽  
Jiang Jiang
Keyword(s):  
Differential Evolution ◽  
Production Planning ◽  
Optimization Algorithm ◽  
Programming Model ◽  
Solution Space ◽  
Defense Industry ◽  
Nonlinear Integer Programming ◽  
Planning Problem ◽  
Proposed Model ◽  
Production Planning Problem

The production planning problem in defense industry has the non-regular nonlinearity of the objective function and the NP-hard nature of the solution space. A nonlinear integer programming model was proposed for this problem. A differential evolution based optimization algorithm was developed to solve the proposed model. A case study validated the effectiveness of the developed algorithm, and proved that it is superior to the standard genetic algorithm on the global searching capability. The algorithm can support the weapons production planning, and also can be applied to other industries.

Application of Multi Objective Fuzzy Linear Programming in Supply Production Planning Problem

2012 ◽  
Author(s):  
Pandian M. Vasant
Keyword(s):  
Linear Programming ◽  
Production Planning ◽  
Membership Function ◽  
Programming Model ◽  
Real Life ◽  
Fuzzy Linear Programming ◽  
Programming Approach ◽  
Planning Problem ◽  
Production Planning Problem ◽  
S Curve

The objective of this paper is to establish the usefulness of modified s-curve membership function in a limited supply production planning problem with continuous variables. In this respect, fuzzy parameters of linear programming are modeled by non-linear membership functions such as s-curve function. This paper begins with an introduction and construction of the modified s-curve membership function. A numerical real life example of supply production planning problem is then presented. The computational results show the usefulness of the modified s-curve membership function with fuzzy linear programming technique in optimising individual objective functions, compared to non-fuzzy linear programming approach. Futhermore, the optimal solution helps to conclude that by incorporating fuzziness in a linear programming model through the objective function and constraints, a better level of satisfactory solution will be provided in respect to vagueness, compared to non-fuzzy linear programming.

scholarly journals Production Planning Problem of a Two-Level Supply Chain with Production-Time-Dependent Products

2021 ◽  
Vol 11 (20) ◽  
pp. 9687
Author(s):  
Jun-Hee Han ◽  
Ju-Yong Lee ◽  
Bongjoo Jeong
Keyword(s):  
Supply Chain ◽  
Production Planning ◽  
Programming Model ◽  
Planning Horizon ◽  
Mixed Integer ◽  
Planning Problem ◽  
Manufacturing Plant ◽  
Production Lines ◽  
Multiple Production ◽  
Production Planning Problem

This study considers a production planning problem with a two-level supply chain consisting of multiple suppliers and a manufacturing plant. Each supplier that consists of multiple production lines can produce several types of semi-finished products, and the manufacturing plant produces the finished products using the semi-finished products from the suppliers to meet dynamic demands. In the suppliers, different types of semi-finished products can be produced in the same batch, and products in the same batch can only be started simultaneously (at the same time) even if they complete at different times. The purpose of this study is to determine the selection of suppliers and their production lines for the production of semi-finished products for each period of a given planning horizon, and the objective is to minimize total costs associated with the supply chain during the whole planning horizon. To solve this problem, we suggest a mixed integer programming model and a heuristic algorithm. To verify performance of the algorithm, a series of tests are conducted on a number of instances, and the results are presented.

scholarly journals The integrated cutting and packing heterogeneous precast beams multiperiod production planning problem  

2021 ◽  
Author(s):  
Kennedy Anderson Gumarães de Araújo ◽  
Tibérius de Oliveira e Bonates ◽  
Bruno Prata
Keyword(s):  
Genetic Algorithm ◽  
Production Planning ◽  
Programming Model ◽  
Optimal Solution ◽  
Planning Problem ◽  
Cutting And Packing ◽  
Novel Variant ◽  
Production Planning Problem ◽  
Genetic Algorithm Approach ◽  
Feasible Solutions

We introduce a novel variant of cutting production planning problems named Integrated Cutting and Packing Heterogeneous Precast Beams Multiperiod Production Planning (ICP-HPBMPP). We propose an integer linear programming model for the ICP-HPBMPP, as well as a lower bound for its optimal objective function value, which is empirically shown to be closer to the optimal solution value than the bound obtained from the linear relaxation of the model. We also propose a genetic algorithm approach for the ICP-HPBMPP as an alternative solution method. We discuss computational experiments and propose a parameterization for the genetic algorithm using D-optimal experimental design. We observe good performance of the exact approach when solving small-sized instances, although there are difficulties in finding optimal solutions for medium and large-sized problems, or even in finding feasible solutions for large instances. On the other hand, the genetic algorithm is shown to typically find good-quality solutions for large-sized instances within short computing times.

scholarly journals A New Extended MILP MRP Approach to Production Planning and Its Application in the Jewelry Industry

2016 ◽  
Vol 2016 ◽  
pp. 1-18 ◽  
Author(s):  
Erhan Yazıcı ◽  
Gülçin Büyüközkan ◽  
Murat Baskak
Keyword(s):  
Production Planning ◽  
Fuzzy Model ◽  
Mixed Integer ◽  
Planning Problem ◽  
Production Environment ◽  
Material Flows ◽  
Proposed Model ◽  
Material Requirement ◽  
Production Planning Problem ◽  
Jewelry Industry

It is important to manage reverse material flows such as recycling, reusing, and remanufacturing in a production environment. This paper addresses a production planning problem which involves reusing of scrap and recycling of waste that occur in the various stages of the production process and remanufacturing/recycling of returns in a closed-loop supply chain environment. An extended material requirement planning (MRP) is proposed as a mixed integer linear programming (MILP) model which includes—beside forward—these reverse material flows. The proposed model is developed for the jewelry industry in Turkey, which uses gold as the primary resource of production. The aim is to manage these reverse material flows as a part of production planning to utilize resources. Considering the mostly unpredictable nature of reverse material flows, the proposed model is likewise transformed into a fuzzy model to provide a better review of production plan for the decision maker. The suggested model is examined through a case study to test the applicability and efficiency.

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