Hybrid Uncertainty-Goal Programming Model with Scaled Index for Production Planning Assessment (original) (raw)
Related papers
Hybrid Uncertainties Modeling for Production Planning Problems
Communications in Mathematics and Applications, 2017
The formulated mathematical model needs pre-determined and precise model parametersto find a solution. However, the model parameters such as coefficient value are usually not precisely known. Coefficient plays a pivotal role sincethe coefficientcouldprovide important information in relationship between algebraic and linguistic expression. Existing method which is commonly used to generate the precise parametric valuesis unable to handle the coexistence of fuzzy information. Moreover, selecting real numbers for coefficients in random process increases the complexity inprogramming process. Hence, we proposed a fuzzy random regression method in this paper to estimate the precise coefficient values which contains fuzzy random information. An illustrative numerical example is provided to deduce coefficient values from different data representation which included the fuzziness and randomness.The coefficients were treated based on the property of fuzzy random regression. The approach resul...
Modeling and Solving Production Planning Problem under Uncertainty: A Case Study
American Journal of Operational Research, 2012
Data in many real life engineering and economical problems suffer fro m inexactness. In the real world there are many forms of uncertainty that affect production processes. Uncertainty always exists in practical engineering problems. in order to deal with the uncertain optimization problems, fuzzy and stochastic approaches are co mmonly used to describe the imprecise characteristics. Herein we assume some intervals in which the data can simultaneously and independently perturb. In this study production planning related data of Al-Araby firm fo r electric sets in Egypt was collected. A production planning model based on linear programming (LP) was formulated. This formulat ion based on the outcomes of collected data. The data includes the amount of required and availab le resources, the demand, the cost of production, the cost of unmet demand, the cost of inventory holding and the revenue. in this work, the objective is to maximize the revenues net of the production, inventory and lost sales costs. The general LP model was solved by using software named W in QSB.
Optimization Production Planning Using Fuzzy Goal Programming Techniques
In the past two decades, ideal planning has been used for the multiple criteria decision making problem solving. The issue is raised here is that how to do a program to achieve the best and most comprehensive program that it has well run ability? Because of costly medical equipment production process, it should pay more attention to production planning. In this research, this was carried out in the company's beta; we are looking to fulfill two objectives, reducing the cost of production, increase revenue leading to increased profits. For the realization of these goals, we use the method of fuzzy planning, according to studies, we use simple collective models and collective weighted method. According to the existing information and problem variables and TIVARY model, we find that the model leads to production costs and increasing income. According to the results of the research, we realized that for the realization of the Beta purposes, we should use TIVARY collective method. This study has expanded the discussion of optimization production planning using fuzzy goal programming techniques. Goal programming was used in various issues such as decision making. The most important goal programming restrictions is unclear goals. Fuzzy goal programming provided, it investigate fuzzy purpose in unknown level.
Solving aggregate production planning problem with uncertainty using fuzzy goal programming
International Journal of Mathematics in Operational Research, 2022
This study proposes a fuzzy goal programming model (FGP) to address planning problem in the work environment, especially in the field of production and the factors affecting production planning, had a great role in increasing the interest in the function of aggregate production planning and everything related to activities and processes that contribute to Products Manufacturing through the optimal use of all available resources in organizations. This paper aimed to solve the problem of aggregate production planning in General Corporation for the Sugar Industry, in a way that helps decision-makers to take appropriate decisions, especially under the fuzzy environment in which all sugar production companies operate, by identifying decision variables, levels of aspiration and tolerance Using the fuzzy goal programming, to reduce the cost of production and storage and the change in the level of the workforce, to help the company meets the market need for the products it produces.
Algorithms, 2019
This paper deals with the modeling and optimization of a bi-level multi-objective production planning problem, where some of the coefficients of objective functions and parameters of constraints are multi-choice. A general transformation technique based on a binary variable has been used to transform the multi-choices parameters of the problem into their equivalent deterministic form. Finally, two different types of secularization technique have been used to achieve the maximum degree of individually membership goals by minimizing their deviational variables and obtained the most satisfactory solution of the formulated problem. An illustrative real case study of production planning has been discussed and, also compared to validate the efficiency and usefulness of the proposed work.
Study Of Fuzzy Goal Programming Model To Production Planning Problems Approach
Jurnal Teknik Informatika C.I.T Medicom
The production planning system can provide satisfaction to the manufacture with the desire target and also with the available raw materials. In achieving the target of goals also face a situation of uncertainty (fuzzy). The aims of this study is proposed the model of fuzzy goal programming approach to optimize production planning system. In this model obtaining maximizing profit and revenue with consider minimize costs of labor cost, raw materials cost, time machine production, and also inventory cost. The numerical example is illustrate that the fuzzy goal programming model can optimize optimize production and profit according desired of decision maker.
Models for production planning under uncertainty: A review
International Journal of Production Economics, 2006
The consideration of uncertainty in manufacturing systems supposes a great advance. Models for production planning which do not recognize the uncertainty can be expected to generate inferior planning decisions as compared to models that explicitly account for the uncertainty. This paper reviews some of the existing literature of production planning under uncertainty. The research objective is to provide the reader with a starting point about uncertainty modelling in production planning problems aimed at production management researchers. The literature review that we compiled consists of 87 citations from 1983 to 2004. A classification scheme for models for production planning under uncertainty is defined. r (J. Mula). Analytical models [3] 3. Material requirement planning Conceptual models [9] Analytical models [6] Artificial intelligence models [4] Simulation models [10] 4. Capacity planning Analytical models [4] Simulation models [1] 5. Manufacturing resource planning Analytical models [7] Artificial intelligence models [5] Simulation models [2] 6. Inventory management Analytical models [10] Artificial intelligence models [5] 7. Supply chain planning Conceptual models [1] Analytical models [5] Artificial intelligence models [5] J. Mula et al. / Int. J. Production Economics 103 (2006) 271-285 272
Production planning under dynamic product environment: a multi-objective goal programming approach
2002
Production planning is a complicated task that requires cooperation among multiple functional units in any organization. In order to design an efficient production planning system, a good understanding of the environment in terms of customers, products and manufacturing processes is a must. Although such planning exists in the company, it is often incorrectly structured due to the presence of multiple conflicting objectives. The primary difficulty in modern decision analysis is the treatment of multiple conflicting objectives. A formal decision analysis that is capable of handling multiple conflicting goals through the use of priorities may be a new frontier of management science. The objective of this study is to develop a multi objective goal programming (MOGP) model to a
Applying fuzzy stochastic programming for multi- product multi-time period production planning
This paper presents an integration of fuzzily imprecise and probabilistically uncertain data in multi-time period production planning problem. We consider fluctuation of demands and resources by a fuzzy stochastic approach due to incomplete and/or unavailable information. A mathematical programming model that incorpo- rates these aspects of uncertainty with grading products based on different qualities is developed to maximize total profit, considering total costs includes cost of production, outsourcing, labor, and holding, with subject to constraints associated with customer satisfaction, demand, and holding inventory. We also extend a new approach of defuzzifying and derandomizing methods by measuring the superiority and inferiority of the fuzzy stochastic variables when the model has fuzzy stochastic parameters both in the constraints and in the objec- tive function. To illustrate the behavior of the proposed model and verify the performance of the developed fuzzy stochastic-based approach, we introduce a number of numerical examples to explain the use of the fore- going approach. Consequently, the results obtained are reported and discussed.