Browsing by Subject "Nonlinear Programming"

Now showing 1 - 5 of 5

Open Access
Aggregate production planning: an application in Özkaşıkçı Flour Mill
(1996) Çağan, Alpas
Aggregate planning is medium-range capacity planning that typically covers a time horizon of anywhere from 3 months to 18 months. The goal of aggregate planning is to achieve a feasible production plan that will effectively utilize the organization’s resources to satisfy expected demand. In this study. Aggregate Production Planning is applied to 0zka?ik9i Flour Mill in order to maximize the total profit by using the optimal allocation of export and domestic sales to the plant capacity. A nonlinear programming (NP) model is developed and the proposed model is run on GAMS (General Algebraic Modeling System) software package. Alternative scenarios are applied to the model in order to find optimal allocation of export and domestic production and to maximize the total profit.
Open Access
An application of stochastic programming on robust airline scheduling
(2014) Karacaoğlu, Nil
The aim of this study is to create flight schedules which are less susceptible to unexpected flight delays. To this end, we examine the block time of the flight in two parts, cruise time and non-cruise time. The cruise time is accepted as controllable within some limit and it is taken as a decision variable in our model. The non-cruise time is open to variations. In order to consider the variability of non-cruise times in the planning stage, we propose a nonlinear mixed integer two stage stochastic programming model which takes the non-cruise time scenarios as input. The published departure times of flights are determined in the first stage and the actual schedule is decided on the second stage depending on the non-cruise times. The objective is to minimize the airline’s operating and passenger dissatisfaction cost. Fuel and CO2 emission costs are nonlinear and this nonlinearity is handled by second order conic inequalities. Two heuristics are proposed to solve the problem when the size of networks and number of scenarios increase. A computational study is conducted using the data of a major U.S. carrier. We compare the solutions of our stochastic model with the ones found by using expected values of non-cruise times and the company’s published schedule.
Open Access
The determination of optimal time-in-grade for promotion at each rank in the Turkish Army
(2001) Şenerdem, Barbaros Hayrettin
The increasing pace of development in Human Resource Management makes an objective promotion system more valid than a system on subjective criteria in the Turkish Army. Therefore, the Army Headquarters tries to adapt an appropriate promotion system and criteria to The Turkish Army’s big hierarchical structure. Thus, the gap between the current and required officer inventory in the promotion system is thought to be minimized.In this study, the validity of a new promotion system, which is still under consideration in Human Resource Department of The Turkish Army, is evaluated against the current promotion system in The Turkish Army to establish a base for further quantitative research. The core of the study focuses on a non-linear optimization problem. The optimization is to obtain optimal values for time to wait at a rank until promotion. Optimal values of the selected promotion criteria, time – in-grade, are thought to make great contribution to further personnel decisions in The Turkish Army’s promotion system. The constructed model also supports the manpower planning requirements of the Army in determining the impact of existing policies on given promotion criteria over the long term.
Open Access
Implementation of a continuation method for nonlinear complementarity problems via normal maps
(1997) Erkan, Ali
In this thesis, a continuation method for nonlinear complementarity problems via normal maps that is developed by Chen, Harker and Pinar [8] is implemented. This continuation method uses the smooth function to approximate the normal map reformulation of nonlinear complementarity problems. The algorithm is implemented and tested with two different plussmoothing functions namely interior point plus-smooth function and piecewise quadratic plus-smoothing function. These two functions are compared. Testing of the algorithm is made with several known problems.
Open Access
Solution of feasibility problems via non-smooth optimization
(1990) Ouveysi, Iradj
In this study we present a penalty function approach for linear feasibility problems. Our attempt is to find an eiL· coive algorithm based on an exterior method. Any given feasibility (for a set of linear inequalities) problem, is first transformed into an unconstrained minimization of a penalty function, and then the problem is reduced to minimizing a convex, non-smooth, quadratic function. Due to non-differentiability of the penalty function, the gradient type methods can not be applied directly, so a modified nonlinear programming technique will be used in order to overcome the difficulties of the break points. In this research we present a new algorithm for minimizing this non-smooth penalty function. By dropping the nonnegativity constraints and using conjugate gradient method we compute a maximum set of conjugate directions and then we perform line searches on these directions in order to minimize our penalty function. Whenever the optimality criteria is not satisfied and the improvements in all directions are not enough, we calculate the new set of conjugate directions by conjugate Gram Schmit process, but one of the directions is the element of sub differential at the present point.