A Multistage Procedure for Optimal Distribution of Preparatory-Year Students to Faculties and Departments: A Mixed Integer Nonlinear Goal Programming Model with Enhanced Differential Evolution Algorithm

2016 ◽  
Vol 13 (11) ◽  
pp. 7847-7863
Author(s):  
Said Ali El-Qulity ◽  
Ali Wagdy Mohamed ◽  
Abdullah O Bafail ◽  
Reda M. S Abdelaal
2014 ◽  
Vol 1046 ◽  
pp. 367-370
Author(s):  
Yu Zhou ◽  
Yong Bin Li ◽  
Zhong Zheng Shi ◽  
Zheng Xin Li ◽  
Lei Zhang

The multistage goal programming model is popular to model the defense projects portfolio optimization problem in recent years. However, as its high-dimensional variables and large-scale solution space, the addressed model is hard to be solved in an acceptable time. To deal with this challenge, we propose an improved differential evolution algorithm which combines three novel strategies i.e. the variables clustering based evolution, the whole randomized parameters, and the child-individual based selection. The simulation results show that this algorithm has the fastest convergence and the best global searching capability in 6 test instances with different scales of solution space, compared with classical differential evolution algorithm (CDE), genetic algorithm (GA) and particle swarm optimization (PSO) algorithm.


2015 ◽  
Vol 2015 ◽  
pp. 1-13 ◽  
Author(s):  
Said Ali El-Quliti ◽  
Abdul Hamid Mohamed Ragab ◽  
Reda Abdelaal ◽  
Ali Wagdy Mohamed ◽  
Abdulfattah Suliman Mashat ◽  
...  

This paper proposes a nonlinear Goal Programming Model (GPM) for solving the problem of admission capacity planning in academic universities. Many factors of university admission capacity planning have been taken into consideration among which are number of admitted students in the past years, total population in the country, number of graduates from secondary schools, desired ratios of specific specialties, faculty-to-students ratio, and the past number of graduates. The proposed model is general and has been tested at King Abdulaziz University (KAU) in the Kingdom of Saudi Arabia, where the work aims to achieve the key objectives of a five-year development plan in addition to a 25-year future plan (AAFAQ) for universities education in the Kingdom. Based on the results of this test, the proposed GPM with a modified differential evolution algorithm has approved an ability to solve general admission capacity planning problem in terms of high quality, rapid convergence speed, efficiency, and robustness.


2016 ◽  
Vol 2016 ◽  
pp. 1-14 ◽  
Author(s):  
Said Ali El-Qulity ◽  
Ali Wagdy Mohamed

This paper proposes a nonlinear integer goal programming model (NIGPM) for solving the general problem of admission capacity planning in a country as a whole. The work aims to satisfy most of the required key objectives of a country related to the enrollment problem for higher education. The system general outlines are developed along with the solution methodology for application to the time horizon in a given plan. The up-to-date data for Saudi Arabia is used as a case study and a novel evolutionary algorithm based on modified differential evolution (DE) algorithm is used to solve the complexity of the NIGPM generated for different goal priorities. The experimental results presented in this paper show their effectiveness in solving the admission capacity for higher education in terms of final solution quality and robustness.


2017 ◽  
Vol 2017 ◽  
pp. 1-15 ◽  
Author(s):  
Lianfei Yu ◽  
Cheng Zhu ◽  
Jianmai Shi ◽  
Weiming Zhang

Efficient scheduling for the supporting operations of aircrafts in flight deck is critical to the aircraft carrier, and even several seconds’ improvement may lead to totally converse outcome of a battle. In the paper, we ameliorate the supporting operations of carrier-based aircrafts and investigate three simultaneous operation relationships during the supporting process, including precedence constraints, parallel operations, and sequence flexibility. Furthermore, multifunctional aircrafts have to take off synergistically and participate in a combat cooperatively. However, their takeoff order must be restrictively prioritized during the scheduling period accorded by certain operational regulations. To efficiently prioritize the takeoff order while minimizing the total time budget on the whole takeoff duration, we propose a novel mixed integer liner programming formulation (MILP) for the flight deck scheduling problem. Motivated by the hardness of MILP, we design an improved differential evolution algorithm combined with typical local search strategies to improve computational efficiency. We numerically compare the performance of our algorithm with the classical genetic algorithm and normal differential evolution algorithm and the results show that our algorithm obtains better scheduling schemes that can meet both the operational relations and the takeoff priority requirements.


Forests ◽  
2020 ◽  
Vol 11 (7) ◽  
pp. 744
Author(s):  
Mehmet Demirci ◽  
Ahmet Yeşil ◽  
Pete Bettinger

A mixed integer goal programming model is developed to address the regeneration planning problems of even-aged forests in the Mediterranean region of Turkey. The unique aspect of the goal programming formulation is to minimize deviations in scheduled wood product volumes and the size of harvest areas within each time period, as these are important goals for the management area. About 98% of the forests in Turkey are considered even-aged, and 2% are uneven-aged. Therefore, an age class method is used for the planning of even-aged forests. For the areas where this method is applied, reaching the optimal age class structure is the first priority. This involves implementing final harvests (clearcuts) to regenerate an amount of forest area into each age class. To meet the local market’s needs, forest enterprises also require the final yield to be fairly equal each year. Further, it is desired that the harvest area (regeneration area) is relatively equal each year, to address operational considerations. A linear goal programming model is developed to address the problem. The minimization of deviations from both the harvest area and harvest volume targets are incorporated as goals in the objective function of the model. Several scenarios are solved using the extended version of Lingo 16. A scenario with weights of 0.8 for area and 0.2 for volume produces the best results. Here, the total deviation for 20 years is 3.8 ha in area and 2889 m3 in volume. In the actual regeneration plan, the area deviation for 10 years is 54.72 ha (6.2% of total regeneration area), and the volume deviation is 20,472 m3 (9.8% of harvest volume). The model described through this study can be developed further and integrated into forest management planning software and processes used for the planning of even-aged forests in the Mediterranean region.


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