Developing optimization models for cross-functional decision-making: integrating marketing and production planning

The present investigation is related to one of the most important processes for the development of life on Earth; photosynthesis, an essential process in the cycle and development of living beings, centered on solar radiation that is useful for plants to carry out this process, Photosynthetically Active Radiation (PAR). The objective of this work is to generate information on the PAR through a database to collaborate in the decision-making of farmers in the area. For this purpose, a quantum sensor installed in building 6 of the UAZ Siglo XXI Campus was used. According to Abal (2013), in agricultural and production planning, it is especially important to have a detailed knowledge of incident solar radiation on the earth's surface (Abal and Durañona, 2013). When collecting, treating and analyzing the data, it was found that the daily average PAR is 819.52 μmol of photons m-2 s-1 (179.47 W m-2), if only the sunny hours are taken into account. It can be concluded that according to the PAR received in the evaluation region and the type of nutrients in the soil, other crop alternatives to those traditionally used can be sought.

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The optimization model of the logging machinery usage in forestry practice

Acta Universitatis Agriculturae et Silviculturae Mendelianae Brunensis ◽

10.11118/actaun200957060105 ◽

2009 ◽

Vol 57 (6) ◽

pp. 105-112 ◽

Cited By ~ 1

Author(s):

Jitka Janová ◽

M. Lindnerová

Keyword(s):

Decision Making ◽

Czech Republic ◽

Decision Support ◽

Decision Support Systems ◽

Optimization Model ◽

Support Systems ◽

Decision Problems ◽

Optimization Models ◽

Ongoing Research ◽

The Impact

The decision support systems commonly used in industry and economy managerial practice for optimizing the processes are based on algoritmization of the typical decision problems. In Czech forestry business, there is a lack of developed decision support systems, which could be easily used in daily practice. This stems from the fact, that the application of optimization methods is less successful in forestry decision making than in industry or economy due to inherent complexity of the forestry decision problems. There is worldwide ongoing research on optimization models applicable in forestry decision making, but the results are not globally applicable and moreover the cost of possibly arising software tools are indispensable. Especially small and medium forestry companies in Czech Republic can not afford such additional costs, although the results of optimization could positively influence not only the business itself but also the impact of forestry business on the environment. Hence there is a need for user friendly optimization models for forestry decision making in the area of Czech Republic, which could be easily solved in commonly available software, and whose results would be both, realistic and easily applicable in the daily decision making.The aim of this paper is to develop the optimization model for the machinery use planning in Czech logging firm in such a way, that the results can be obtained using MS EXCEL. The goal is to identify the integer number of particular machines which should be outsourced for the next period, when the total cost minimization is required. The linear programming model is designed covering the typical restrictions on available machinery and total volume of trees to be cut and transported. The model offers additional result in the form of optimal employment of particular machines. The solution procedure is described in detail and the results obtained are discussed with respect to its applicability in practical forestry decision making. The possibility of extension of suggested model by including additional requirements is mentioned and the example for the wood manipulation requirement is shown.

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Research of Driver Automatic Alarm Decision-Making Optimization Models with Precision Clock Scanning

CICTP 2014 ◽

10.1061/9780784413623.243 ◽

2014 ◽

Author(s):

Feng-yuan Jia ◽

Zhi-chao Guan ◽

Lian Huang ◽

Hai-xiang Zou ◽

Chun-yan Li

Keyword(s):

Decision Making ◽

Optimization Models ◽

Precision Clock

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Experiences in Modeling, Simulation, and Optimization of Chemical Industry Supply Chains

Manufacturing ◽

10.1115/imece2002-33606 ◽

2002 ◽

Author(s):

Charles R. Standridge ◽

David R. Heltne

Keyword(s):

Supply Chain ◽

Simulation Model ◽

Production Planning ◽

Simulation Optimization ◽

Process Industry ◽

Plant Production ◽

Optimization Models ◽

Individual Plant ◽

Simulation And Optimization ◽

Combined Simulation

We have developed and applied simulation as well as combined simulation – optimization models to represent process industry plant logistics and supply chain operations. The simulation model represents plant production, inventory, and shipping operations as well as inter-plant shipments. When a combined simulation-optimization approach is used, the simulation periodically invokes a classical production planning optimization model to set production and shipping levels. These levels are retrieved by and used in the simulation model. Process industry supply chain operations include stochastic elements such as customer demands whose expected values may vary in time as well as transportation lead times. The complexity of individual plant operations and logistics must be considered. Simulation provides the methods needed to integrate these elements in a single model. Periodically during a simulation run, production planning decisions that require optimization models may be made. Simulation experimental results are used to determine service levels to end customers as well as to set rail fleet sizes, inventory capacities, and capital equipment requirements for logistics as well as to assess alternative shipping schedules.

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Fostering linguistic decision-making under uncertainty: A proportional interval type-2 hesitant fuzzy TOPSIS approach based on Hamacher aggregation operators and andness optimization models

Information Sciences ◽

10.1016/j.ins.2019.05.074 ◽

2019 ◽

Vol 500 ◽

pp. 229-258 ◽

Cited By ~ 31

Author(s):

Zhen-Song Chen ◽

Yi Yang ◽

Xian-Jia Wang ◽

Kwai-Sang Chin ◽

Kwok-Leung Tsui

Keyword(s):

Decision Making ◽

Fuzzy Topsis ◽

Aggregation Operators ◽

Optimization Models ◽

Decision Making Under Uncertainty ◽

Linguistic Decision Making ◽

Topsis Approach ◽

Interval Type

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A Production Planning Model for Make-To-Order Companies with Capacity Constraint

Advanced Materials Research ◽

10.4028/www.scientific.net/amr.201-203.1066 ◽

2011 ◽

Vol 201-203 ◽

pp. 1066-1069 ◽

Cited By ~ 1

Author(s):

Hua Li Gao ◽

Bin Dan ◽

You Guo Jing

Keyword(s):

Decision Making ◽

Production Planning ◽

Production Systems ◽

Optimal Solution ◽

Capacity Constraint ◽

Planning Model ◽

Numerical Example ◽

Make To Order ◽

Decision Making Model

This paper proposes a decision-making model of the planning quantity put into production for Make-To-Order (MTO) companies with capacity constraint. The low repeatability and the uncertain products eligibility-rate of the MTO production systems are fully taken into account, and an optimal solution is presented. Finally, a numerical example is given to illustrate the validity of the model.

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Satisfaction Degree Based Interactive Decision Making under Hesitant Fuzzy Environment with Incomplete Weights

International Journal of Uncertainty Fuzziness and Knowledge-Based Systems ◽

10.1142/s0218488514500275 ◽

2014 ◽

Vol 22 (04) ◽

pp. 553-572 ◽

Cited By ~ 41

Author(s):

Huchang Liao ◽

Zeshui Xu

Keyword(s):

Decision Making ◽

Hesitant Fuzzy Set ◽

Optimization Models ◽

Multi Criteria Decision Making ◽

Ideal Solution ◽

Fuzzy Information ◽

Satisfaction Degree ◽

Interactive Decision Making ◽

New Research ◽

Topsis Technique

Multi-criteria decision making with hesitant fuzzy information is a new research topic since the hesitant fuzzy set was firstly proposed. This paper investigates a multi-criteria decision making problem where the weight information is partially known. We firstly propose the hesitant fuzzy positive ideal solution and the hesitant fuzzy negative ideal solution. Motivated by the TOPSIS (Technique for Order Preference by Similarity to an ideal Solution) method, we definite the satisfaction degree of an alternative, based on which several optimization models are derived to determinate the weights. Subsequently, in order to make a more reasonable decision, we introduce an interactive method based on some optimization models for multi-criteria decision making problems with hesitant fuzzy information. Finally, a practical example on evaluating the service quality of airlines is provided to illustrate our models and method.

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