Topic
Goal programming
About: Goal programming is a research topic. Over the lifetime, 4330 publications have been published within this topic receiving 117758 citations.
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TL;DR: In this article, a goal programming-based multiple-objective integrated response and recovery model is presented to investigate strategic supply distribution and early-stage network restoration decisions, given limited capacity, budget, and available resources.
92 citations
TL;DR: A single-phase goal programming algorithm for scheduling nurses in one unit of the hospital and nurses' preferences for weekends on and off is presented.
Abstract: This paper presents a single-phase goal programming algorithm for scheduling nurses in one unit of the hospital. The goals represent the scheduling policies of the hospital and nurses' preferences for weekends on and off. An application to one unit of the hospital with 11 nurses resulted in satisfactory schedules. The computer time to solve the problem using a goal programming algorithm was very reasonable.
91 citations
TL;DR: In this article, a hybrid model for selection and costs assessment is proposed to address inter-relationships among CSR criteria using trial and evaluation laboratory methods, analytical network processes and zero-one goal programming.
90 citations
TL;DR: In this article, the power-pressure mapping problem is formulated as a multiobjective optimization problem and solved with nonlinear goal programming, which provides a single solution from the set of all multi-objective optimal solutions based on the assignment of relative preference values to the objective functions.
Abstract: Coordinated control schemes, at fossil fuel power plants, drive units as a whole through a variable pressure operating policy. Ordinarily, the pressure control loop set-point is obtained from the unit load demand through a fixed nonlinear mapping that does not allow for process optimization under operating conditions different from the originals. This paper presents a procedure to optimally design the power-pressure mapping by defining and solving a multiobjective optimization problem. Both procedure and mapping are realized as a supervisory set-point scheduler. The optimization problem is solved with the nonlinear goal programming method, which provides a single solution from the set of all multiobjective optimal solutions based on the assignment of relative preference values to the objective functions. This approach provides a way to specify the operating policy to accommodate a great diversity of operating scenarios. The procedure is presented through a case study, and its feasibility is demonstrated via simulation experiments.
89 citations
TL;DR: In this paper, the authors studied the application of multiobjective optimization techniques to structural design problems involving uncertain parameters and random processes and found that the game theory approach is superior in finding a better optimum solution, assuming the proper balance of the various objective functions.
Abstract: The application of multiobjective optimization techniques to structural design problems involving uncertain parameters and random processes is studied. The design of a cantilever beam with a tip mass subjected to a stochastic base excitation is considered for illustration. Several of the problem parameters are assumed to be random variables and the structural mass, fatigue damage, and negative of natural frequency of vibration are considered for minimization. The solution of this three-criteria design problem is found by using global criterion, utility function, game theory, goal programming, goal attainment, bounded objective function, and lexicographic methods. It is observed that the game theory approach is superior in finding a better optimum solution, assuming the proper balance of the various objective functions. The procedures used in the present investigation are expected to be useful in the design of general dynamic systems involving uncertain parameters, stochastic process, and multiple objectives.
89 citations