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...
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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.
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...
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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...
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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.
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...
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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.
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...
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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.
Medicine residency is three to seven years of challenging graduate medical training that puts a lot of mental and physiological burden over the residents. Like other surgical branches, anesthesia and reanimation depar...
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Medicine residency is three to seven years of challenging graduate medical training that puts a lot of mental and physiological burden over the residents. Like other surgical branches, anesthesia and reanimation departments provide 24 h continuous service and the residents are the main providers of this service. The residents are assigned for on-call shifts during their training, as well as working during the regular day shifts. These schedules must address several considerations like preferences of the residents and coverage requirements of two different locations: the intensive care unit (ICU) and the surgery room (SR). In this study we develop a goal programming (GP) model for scheduling the shifts of the residents in the Anesthesia and Reanimation Department of Bezmialem Vakif University Medical School (BUMS). The rules that must be strictly met, like the number of on-duty shifts or preventing block shifts, are formulated as hard constraints. The preferences of the residents like increasing the number of weekends without shifts and assigning duties on the same night to the same social groups are formulated as soft constraints. The penalties for the deviation from the soft constraints are determined by the analytical hierarchy process (AHP). We are able to solve problems of realistic size to optimality in a few seconds. We showed that the proposed formulation, which the department uses currently, has yielded substantial improvements and much better schedules are created with less effort. (C) 2012 Elsevier Ltd. All rights reserved.
In this study, an Analytic Hierarchy Process (AHP) and goal programming-based solution approach for the student-project team formation problem is proposed. In the first and second phases of a two-phase goal programmin...
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In this study, an Analytic Hierarchy Process (AHP) and goal programming-based solution approach for the student-project team formation problem is proposed. In the first and second phases of a two-phase goal programming-based approach developed in a recent study of authors, students and advisers are allocated to project teams considering several criteria. The AHP method is used to determine the criteria weights for the goal programming models. Surveys are conducted with students and advisors to determine the criteria weights for each student and advisor. Since the criteria weights are different for different decision makers, a distance-based non-linear (DBNL) mathematical programming model is used to determine a group decision. The proposed approach is implemented on a real-life project-team formation problem. The results are compared with the real-life allocations in terms of the problem criteria considered in the study and it is observed that our approach produces significantly more satisfactory results. Additionally, although it takes a considerable amount of time to perform the allocations in real-life, using the proposed approach, allocations can be performed in a few hours, including the only once-conducted survey time. The presented approach is proposed for a special problem in this study;however, it can be easily adapted to other project-team formation problems.
This paper presents fuzzy goal programming using with exponential membership function, which uses the modeling, and solving of health care system for optimal efficient management. The limited human resources and budge...
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This paper presents fuzzy goal programming using with exponential membership function, which uses the modeling, and solving of health care system for optimal efficient management. The limited human resources and budget in a health-care organization are described with fuzzy conditions for determine the future strategies for unknown situations. In this study, the exponential membership function is preferred dynamic situation in next period. The study aims to assign the resources for optimization with enable management to meet the fuzzy objective of minimizing the system costs while patients are satisfied. The fuzzy goals are identified and prioritized for the strategic planning and resource allocation. A fuzzy goal-programming model is illustrated using the data provided by a health-care organization in Turkey-Sakarya private hospital. (C) 2014 Elsevier Ltd. All rights reserved.
This paper presents a goal programming (GP) procedure for fuzzy multiobjective linear fractional programming (FMOLFP) problems. In the proposed approach, which is motivated by Mohamed (Fuzzy Sets and Systems 89 (1997)...
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This paper presents a goal programming (GP) procedure for fuzzy multiobjective linear fractional programming (FMOLFP) problems. In the proposed approach, which is motivated by Mohamed (Fuzzy Sets and Systems 89 (1997) 215), GP model for achievement of the highest membership value of each of fuzzy goals defined for the fractional objectives is formulated. In the solution process, the method of variable change on the under- and over-deviational variables of the membership goals associated with the fuzzy goals of the model is introduced to solve the problem efficiently by using linear goal programming (LGP) methodology. The approach is illustrated by two numerical examples. (C) 2002 Elsevier B.V. All rights reserved.
This paper provides a survey of the literature on goal programming (GP) from 1970 through 1982. Almost 300 references of methodological and applied papers on GP are categorized according to 18 areas of application and...
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This paper provides a survey of the literature on goal programming (GP) from 1970 through 1982. Almost 300 references of methodological and applied papers on GP are categorized according to 18 areas of application and according to 12 different variants of GP. [ABSTRACT FROM AUTHOR]
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