Strategic mine planning and waste management are an important aspect of surface mining operations. Recent environmental and regulatory requirements make waste management an integral part of mine planning in the oil sa...
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Strategic mine planning and waste management are an important aspect of surface mining operations. Recent environmental and regulatory requirements make waste management an integral part of mine planning in the oil sands industry. The research problem here is determining the order of extraction of ore, dyke material and waste to be removed from a predefined ultimate pit limit over the mine life that maximises the net present value of the operation. We have developed, implemented, and tested a proposed mixed integer goal programming theoretical framework for oil sands open pit production scheduling with multiple material types. The formulation uses binary integer variables to control mining precedence and continuous variables to control mining of ore and dyke material. There are also goal deviational variables and penalty costs and priorities that must be set up by the planner. The optimisation model was implemented in TOMLAB/CPLEX environment. The developed model proved to be able to generate a uniform schedule for ore and dyke material. This is in line with recent regulatory requirements by Alberta Energy Resources and Conservation Board (Directive 074) which requires oil sands mining companies to develop life of mine plans which ties in to their in-pit tailings disposal strategy. It also provides a practical mining sequence that is consistent with mining oil sands deposit. Similarly, tradeoffs between achieving a goal and maximising NPV can be made.
In goal programming model, the best solution is established in such a way that the sum of the weighted deviations from the goals is minimal. The weight factor of a given objective is composed of two components destine...
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In goal programming model, the best solution is established in such a way that the sum of the weighted deviations from the goals is minimal. The weight factor of a given objective is composed of two components destined to represent two different roles. The first one is "normalization" meaning to bring all deviations to a common unit of measurement based on the degree of proximity to the goal. The second is "valorization" reflecting the decision-maker's preference structure. The weight factor related to an objective is not a simple constant but a function of the realized level of objectives. Because of this variable nature of the weights this model will be non-linear. To cope with this problem we intend to obtain an equivalent linear presentation so that the problem can be solved using standard software suitable for mixed linear programs. (C) 2003 Elsevier Ltd. All rights reserved.
The United Nations agenda for sustainable development by the year 2030 proposes 17 sustainable development goals which include access to affordable, reliable and clean energy, sustained economic growth with full produ...
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The United Nations agenda for sustainable development by the year 2030 proposes 17 sustainable development goals which include access to affordable, reliable and clean energy, sustained economic growth with full productive employment and, urgent action to mitigate environmental degradation. Planning for sustainable development requires integrating conflicting criteria on economy, energy, environment and social aspects. In this paper, we introduce a Weighted goal programming model involving criteria on the economic development (GDP), the electricity consumption, the greenhouse gas emissions, and the total number of employees to determine optimal labor allocation across various economic sectors. The proposed model is validated with data from the six members of the Gulf Cooperation Council (namely Bahrain, Kuwait, Oman, Qatar, Saudi Arabia and the United Arab Emirates). The results of the model aim to provide empirical evidence and insights to decision makers and policy analysts in developing optimal strategies able to simultaneously satisfy energy demand, economic growth, labor development and reduction in greenhouse gas emissions to achieve sustainability targets by the year 2030. (C) 2016 Elsevier Ltd. All rights reserved.
Facility location-allocation (FLA) decisions play a significant role in the performance of supply network in many practical applications, such as emergency service system, supply chain system, public service system, e...
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Facility location-allocation (FLA) decisions play a significant role in the performance of supply network in many practical applications, such as emergency service system, supply chain system, public service system, etc. In this paper, a multi-criteria model (including multi-attribute and multi-objective) for optimal and efficient facility location-allocation patterns was proposed. We first utilize multi attribute decision making (MADM) method-DEA to evaluate the relative efficiency of each potential location, and then combine the efficiency identified from DEA as a goal in a multi objective decision making (MODM) framework by using goal programming. A hypothetical example is presented to illustrate the effectiveness and the efficiency of the proposed model. Results demonstrate that the proposed multi-criteria model is an effective tool for generating a set of more realistic and flexible optimal solution in solving facility location-allocation problems by adjusting the goal priorities with respect to the importance of each objective and the aspiration level with respect to desired target values. The proposed model is also flexible and general enough to consider other specific location decisions such as emergency facilities, undesirable facilities and supply chain design by combing specific location modeling goal with the DEA model.
goal programming with fractional objectives can be reduced to mathematical programming with a linear objective under linear and quadratic constraints, thus optimal solutions can be obtained by using existing Global Op...
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goal programming with fractional objectives can be reduced to mathematical programming with a linear objective under linear and quadratic constraints, thus optimal solutions can be obtained by using existing Global Optimization techniques. However, only heuristic procedures are suggested in the literature on the field. In this note we explore the practical applicability of a recent algorithm for nonconvex quadratic programming with quadratic constraints for this problem. Encouraging computational experiences for randomly generated instances with up to 14 fractional objectives are presented.
The solid transportation problem (STP) is a three-dimensional optimization problem concerned with minimizing total costs while meeting supply and demand limitations by utilizing a variety of transportation modes, refe...
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The solid transportation problem (STP) is a three-dimensional optimization problem concerned with minimizing total costs while meeting supply and demand limitations by utilizing a variety of transportation modes, referred to as conveyances. This study examines the application of the STP to a logistic problem related to the milk distribution problem. Here, the goal is to efficiently deliver milk from a production facility to multiple retail outlets, considering both the cost of transportation and time of delivery as the two primary objectives of the solid transportation problem. Hence, the bi-objective solid transportation problem (BOSTP) is solved, supposing its constraints are fuzzy due to various unpredictable factors during the transportation period. These uncertain values are initially de-fuzzified into the equivalent crisp values using the alpha-cut approach. Later, the STP is solved with single objectives at once using Vogel's approximation method. This mathematical model is then formulated to optimize the total transportation cost and time and solved using the hierarchical order goal programming technique to determine the most cost-effective and time-efficient route. The results show that the hierarchical order goal programming technique minimizes the total transportation cost and time while improving the effectiveness of milk distribution.
The purpose of this article is to draw a comparison between linear programming and goal programming with respect to the assignment model. The presentation of goal programming attempts to strike a balance between theor...
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goal programming (GP) can be regarded as one of the most widely used multicriteria decision-making techniques. In this paper, two surveys are carried out. First, the evolution of GP since its birth to the present time...
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goal programming (GP) can be regarded as one of the most widely used multicriteria decision-making techniques. In this paper, two surveys are carried out. First, the evolution of GP since its birth to the present time, in terms of number of publications, references, journals, etc., has been studied. Second, a more in-depth survey has been carried out, which covers the publications from year 2000 to the present time. All the references are listed, and some conclusions and future research lines have been extracted about the late trends of GP. Copyright (C) 2010 John Wiley & Sons, Ltd.
The aim of this paper is to develop a goal programming nutrition optimization model to meet daily nutrients needs of the reference woman and the reference man subject to the available household budget. Objective funct...
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ISBN:
(纸本)9783901509919
The aim of this paper is to develop a goal programming nutrition optimization model to meet daily nutrients needs of the reference woman and the reference man subject to the available household budget. Objective function in the model is designed in a way to minimize deviations from the defined micronutrients and macronutrients needs as well as from the food cost. The nutrients needs are determined according the World Health Organization (WHO) standards and are incorporated in the model constraints. The sample in this research consists of 55 most frequently used food items as decision variables which are selected based on a survey of 50 households in the capital of Bosnia and Herzegovina. As the result, the solution of the model is optimal selection of the food intake, subject to minimize deviations from the defined goals.
This article identifies differences and similarities between DEA (Data Envelopment Analysis) and DB (Discriminant Analysis) in the view of GP (Coal programming). Based upon such characterization, this article proposes...
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This article identifies differences and similarities between DEA (Data Envelopment Analysis) and DB (Discriminant Analysis) in the view of GP (Coal programming). Based upon such characterization, this article proposes a new type of DA technique, referred to as "DEA-Discriminant Analysis (DEA-DA)", that incorporates a methodological strength of DEA into the DA formulation. This research applies the proposed DEA-DA method to both an illustrative data set and a real case study related to Japanese banks. The importance of DEA-DA is confirmed by comparing it with other DA methods. (C) 1999 Elsevier Science B.V. All rights reserved.
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