The notion of robust goal programming (RGP) using cardinality-constrained robustness via interval-based uncertainty was first examined over a decade ago. Since then, the RGP methodology has not been widely researched,...
详细信息
The notion of robust goal programming (RGP) using cardinality-constrained robustness via interval-based uncertainty was first examined over a decade ago. Since then, the RGP methodology has not been widely researched, specifically when considering different uncertainty sets to implement. Within this context, this paper compares interval-based and norm-based uncertainty sets using cardinality-constrained robustness. Strict robustness using ellipsoidal uncertainty sets is also examined in the RGP realm. The aforementioned methods are demonstrated for a simple instance from the literature, and the results are summarized. Conclusions are made regarding the proposed RGP models when likened to a similar RGP model seen in the literature. Further, the suitability of each RGP model is offered when a decision maker's risk preference or computing availability are taken into consideration. Inferences are made regarding the effectiveness of each uncertainty set in the context of solutions that are relatively unaffected by data uncertainty - that is, robust solutions. Published by Elsevier B.V.
This study presents a fuzzy logic and binary-goal programming-based approach for solving the exam timetabling problem to create a balanced-exam schedule. To be able to address the practical challenges of the exam time...
详细信息
This study presents a fuzzy logic and binary-goal programming-based approach for solving the exam timetabling problem to create a balanced-exam schedule. To be able to address the practical challenges of the exam timetabling problem, the model is developed with and verified by a human expert for exam scheduling. We propose a fuzzy-criticality level identification methodology to assign the criticality levels of exams for the students using three pieces of information, namely, credits, success ratios, and types of the classes. It is noted that the computed criticality levels are close approximates for those of the human expert. We then present a goal programming model to schedule exams using these criticality levels as well as other general problem data. The result of the goal program is a balanced-exam schedule in terms of exam criticality levels. Final step includes room assignments using a simple algorithm. The significance of the study is the consideration of the exam criticalities, for not only the students of the same year but also the students with different levels of seniority, as well as an even distribution of exams for professors which make the problem more challenging for the human expert in practice. Using a real-life problem, we show that our approach creates an exam schedule that is more preferable than the one prepared by the human expert. Additionally, computational results show the potential of our model to be used in real-life problems of larger-size.
We propose a path following method to find the Pareto optimal solutions of a box-constrained multiobjective optimization problem. Under the assumption that the objective functions are Lipschitz continuously differenti...
详细信息
We propose a path following method to find the Pareto optimal solutions of a box-constrained multiobjective optimization problem. Under the assumption that the objective functions are Lipschitz continuously differentiable we prove some necessary conditions for Pareto optimal points and we give a necessary condition for the existence of a feasible point that minimizes all given objective functions at once. We develop a method that looks for the Pareto optimal points as limit points of the trajectories solutions of suitable initial value problems for a system of ordinary differential equations. These trajectories belong to the feasible region and their computation is well suited for a parallel implementation. Moreover the method does not use any scalarization of the multiobjective optimization problem and does not require any ordering information for the components of the vector objective function. We show a numerical experience on some test problems and we apply the method to solve a goal programming problem.
This paper illustrates the application of “fuzzy subsets” concepts to goal programming in a fuzzy environment. In contrast to a typical goal‐programming problem, the goals are stated imprecisely when the decision e...
详细信息
In the past three decades, the magnitude of business dynamics has increased rapidly due to increased complexity, uncertainty and risk of international projects. This fact made it increasingly tough to 'go alone...
详细信息
In the past three decades, the magnitude of business dynamics has increased rapidly due to increased complexity, uncertainty and risk of international projects. This fact made it increasingly tough to 'go alone' into the international projects. As a consequence, companies with diverse strengths and weaknesses cooperatively bid for joint ventures (JV) formation. Joint venture is also a well-established aspect of the crude oil industry, specifically in the upstream segment. Making decision on the optimal form of JVs is still a challenging problem. In addition, the success of a JV is intertwined with the accuracy of the partner selection phase. Therefore, this paper formulates a multi-criteria mathematical model to select the best partners and form an optimal JV for undertaking oilfield projects. The lexicographic goal programming technique is employed to minimise undesirable deviations from diverse goals such as resources needs (technological and expertise), budgetary requirements, time, etc. The model is validated with a real-life-based example and provides insightful views on alternative formats of cooperation.
Product packaging has a huge impact on the efficiency of supply chain activities. In this research, the concept of Design for Assembly (DFA), proved in earlier studies to be effective at improving product manufacturin...
详细信息
Product packaging has a huge impact on the efficiency of supply chain activities. In this research, the concept of Design for Assembly (DFA), proved in earlier studies to be effective at improving product manufacturing operations, is applied to the packaging system. We formulate the packaging system as a mathematical model for three different objectives. With respect to the continual rise in attention paid to sustainability, this research adds sustainability as one of the primary objectives. A case study demonstrates that the proposed model can achieve desired results and reveals a level of consistency among the three objectives. In addition to the application of DFA concepts to a packaging system, the contributions of this research lie in the development of a mathematical model (using integer programming and goal programming) for calculating the cost, handling time, and sustainability of the objectives in line with the design needs of the multi-level packaging size from the perspective of a supply chain to provide a range of solutions offering increased options for firms.
An application of the min-max goal programming methodology to a system of multipurpose reservoirs for optimal monthly operation has been presented in this paper. The goal programming approach possesses significant adv...
详细信息
An application of the min-max goal programming methodology to a system of multipurpose reservoirs for optimal monthly operation has been presented in this paper. The goal programming approach possesses significant advantages because of the fact that it may be based on physical operating criteria. The system goals and constraints are expressed deterministically. A constraint must be strictly satisfied, while for a goal it is desired to achieve the solution, which is as close as possible to the specified target. The min-max goal programming model is developed and applied to the Mahanadi Reservoir Project (MRP) Complex comprising of six multipurpose reservoirs in the state of Madhya Pradesh, India. The MRP Complex operations resulting from the use of the min-max goal programming model are compared to the operations resulting from three other reported optimization models with the same data set for the same operation period. The set of operations resulting from various models are comparable in their effectiveness, and in most aspects the min-max goal programming model operations are better.
Let us consider i = 1, 2,...n alternative forest plans to be evaluated according to j = 1, 2,...m indicators of sustainability. An expert or panel of experts suggests a set of targets or desirable levels of achievemen...
详细信息
Let us consider i = 1, 2,...n alternative forest plans to be evaluated according to j = 1, 2,...m indicators of sustainability. An expert or panel of experts suggests a set of targets or desirable levels of achievement for the in indicators of sustainability considered. Within this context, an important problem is to determine the system with a higher level of achievement with respect to the targets attached by the expert to the in indicators. A natural extension of this problem involves determining a ranking of the n systems considered. A general procedure based on discrete goal programming is proposed to address these problems. The methodology is applied in a case study of a Spanish forest. (C) 2004 Elsevier Ltd. All rights reserved.
This article proposes a novel methodology that employs a goal programming technique and genetic algorithm for formulation and evaluation of a multi-objective function, respectively, for optimal planning of distributed...
详细信息
This article proposes a novel methodology that employs a goal programming technique and genetic algorithm for formulation and evaluation of a multi-objective function, respectively, for optimal planning of distributed generator units in the distribution system. The multi-objective function consists of various performance indices that govern the optimal operation of a distribution system with distributed generator units. The proposed method aims to greatly diminish the dependence in existing methods on the global preference information of the distribution system planner by means of simplicity in problem formulation utilizing a goal programming technique. The capacity of the distribution system to accept distributed generator integration is evaluated such that with the placement of every additional distributed generator unit, the value of multi-objective function reduces without any violation in the system operating constraints. The effectiveness of the proposed method is tested using various distribution systems of different sizes and configurations, and the results are validated with the existing methods, namely the iterative genetic algorithm method and the fuzzy embedded genetic algorithm method. Further, different types of distributed generator models are also employed to demonstrate the adaptability of the proposed method in distributed generator planning studies.
goal programming (GP) and fuzzy programming (FP) are two approaches for solving the vector optimization problem by reducing it to a single (or sequential) objective one. These two approaches have some similarities and...
详细信息
goal programming (GP) and fuzzy programming (FP) are two approaches for solving the vector optimization problem by reducing it to a single (or sequential) objective one. These two approaches have some similarities and both of them have more than one form to handle the multiobjective problem. This paper highlights the similarities between GP and FP and answers the question how each one can lead to the other. However, we will consider in this paper the min-operator to transform the linear FP to a crisp program since this approach is more popular and applied than the others. In addition, some new forms of fuzzy programs are presented in this paper. These new forms use the concept of deviational variables of GP (and not the min-operator) to transform the FP to a crisp one. Finally, a numerical example to illustrate the relationship between the two approaches is given. (C) 1997 Elsevier Science B.V.
暂无评论