Muzaffer Kapanoglu - Academia.edu (original) (raw)
Papers by Muzaffer Kapanoglu
This study deals with the problem of air transportation in Turkish Air Force. The Turkish Air For... more This study deals with the problem of air transportation in Turkish Air Force. The Turkish Air Force has different cargo aircraft to be used in air transportation operations, located in different airbases. The cargo aircraft are loaded cargo, equipment, personnel, repaired items etc. from one of airbases and transport them to the demanding airbases. In this military flight network, each airbase is a demand and support point for different kinds of items. Pickup and delivery demands are known deterministically. There are several operational constraints. The objective of the problem is to find a feasible set of routes for the cargo aircraft so that all requests are serviced, and such that the overall cost is minimized. Problem in hand is modeled and solved as multi-commodity, multi depot and heterogeneous vehicle pickup and delivery problem.
Bu kaynak, Moodle'in 1.7-1.9 versiyonarina yoneliktir. Yeni versiyonu icin yazar veya bolumle... more Bu kaynak, Moodle'in 1.7-1.9 versiyonarina yoneliktir. Yeni versiyonu icin yazar veya bolumle gorusunuz.
Journal of Aeronautics and Space Technologies, 2011
The aircraft routing is the process of assigning each individual aircraft within each fleet to fl... more The aircraft routing is the process of assigning each individual aircraft within each fleet to flight legs. The Federal Aviation Rules require the maintenance of all the aircrafts after specified hours of period as mandatory. The minimum total maintenance cost is provided as a result of the lost flight time which is brought to minimum. The common policies in this business sector follow the practices the maintenance of an aircraft once in 3-4 days periodically. This policy minimizes the risk of grounding of aircraft in the cost of the lost flight hours. In this study, we propose a concurrent, mathematical modeling approach for daily flight route and maintenance scheduling based on recorded flight hours. The model has been solved using CPLEX/GAMS MILP Software. The proposed approach was applied to the daily flight route-maintenance schedule problems of the domestic flights of two companies.
The steelmaking process consists of two phases: primary steelmaking and finishing lines. The sche... more The steelmaking process consists of two phases: primary steelmaking and finishing lines. The scheduling of the continuous galvanizing lines (CGL) is regarded as the most difficult process among the finishing lines due to its multi-objective and highlyconstrained nature. In this paper, we present a multi-population parallel genetic algorithm (MPGA) with a new genetic representation called k nearest neighbor representation, and with a new communication operator for performing better communication between subpopulations in the scheduling of CGL. The developed MPGA consists of two phases. Phase one generates schedules from a primary work in process (WIP) inventory filtered according to the production campaign, campaign tonnage, priorities of planning department, and the due date information of each steel coil. If the final schedule includes the violations of some constraints, module two repairs these violations by using a secondary WIP inventory of steel coils. The developed scheduling ...
A dispatching policy can be defined as a set of condition-action (CA) rules in which changing job... more A dispatching policy can be defined as a set of condition-action (CA) rules in which changing job-shop circumstances (such as number of waiting jobs in queues, machine queue lengths in minutes or hours, overall system utilization, machine utilizations, material transport equipment utilizations, work-in-process, and the like) correspond to the condition part and the dispatching rules (shortest processing time first, earliest due date, modified due date, critical ratio, and the like) correspond to the action part. Having considered the fact that advanced manufacturing technologies can enable job shops to practice dispatching policies as efficient as dispatching rules, this paper introduces an intelligent scheduling system that can learn dispatching policies depending on the queue lengths of machines by using Pitts approach of genetics-based machine learning (GBML) for dynamic job shops. In our proposed intelligent scheduling system, the Pitts approach of GBML performs a matching betwe...
Journal of the Faculty of Engineering and Architecture of Gazi University
Thesis (Ph. D.)--University of South Florida, 1997. Includes bibliographical references (leaves 1... more Thesis (Ph. D.)--University of South Florida, 1997. Includes bibliographical references (leaves 187-193).
Türk Sivil Havacılık sektörü, 2002-2008 yılları arasında gelişen ekonomi ve havacılık alanındaki ... more Türk Sivil Havacılık sektörü, 2002-2008 yılları arasında gelişen ekonomi ve havacılık alanındaki bazı kısıtlamaların kaldırılmasıyla % 53 oranında büyümüştür. Havayolu sektöründe başarılı uluslararası firmalar planlama ve çizelgeleme problemlerini çözmede gelişmiş bilgisayar-destekli çözüm yöntemleri kullanmaktadır. Bu yöntemler işletmelere ciddi rekabet üstünlüğü sağlamaktadır. Havayolu sektöründe dört temel operasyonel planlama ve çizelgeleme problemi bulunmaktadır: uçuş çizelgeleme, uçak çizelgeleme, ekip çizelgeleme ve düzensiz olayların yönetimi. Tüm havayolu işletmelerinin karşı karşıya kaldığı söz konusu operasyonel planlama ve çizelgeleme problemleri bu çalışmada ayrıntılı olarak incelenmiştir. İncelemeler, işletmelerin söz konusu yöntemleri kullanarak maliyetlerinde önemli kazanımlar sağladığını ortaya koymaktadır. Bununla birlikte, büyük ölçekli problemlerin çözümü için gereken süre karar vericilerin arzu ettikleri karar kalitesini tatmin etmeyebilmektedir. Böylesi durumlarda gelişmiş teknolojilerle bütünleştirilmiş modern karar yöntemlerinin kullanılması da işletmelere ciddi maliyet üstünlüğü fırsatı sunmaktadır.
Batch Processing Systems Engineering, 1996
This paper introduces a multi -population genetic algorithm (M-PPGA) using a new genetic represen... more This paper introduces a multi -population genetic algorithm (M-PPGA) using a new genetic representation, the kth-nearest neighbor representation, for Euclidean Traveling Salesman Problems. The proposed M-PPGA runs M g reedy genetic algorithms on M separate populations, each with two new operators, intersection repairing and cheapest insert. The M-PPGA finds optimal or near optimal solutions by using a novel communication operator
Lecture Notes in Computer Science, 2006
Abstract. The steelmaking process consists of two phases: primary steelmaking and finishing lines... more Abstract. The steelmaking process consists of two phases: primary steelmaking and finishing lines. The scheduling of the continuous galvanizing lines (CGL) is regarded as the most difficult process among the finishing lines due to its multi-objective and highly-constrained nature. ...
Lecture Notes in Computer Science, 2006
The facility layout problems in today's batch-to-mass manufacturing systems have gained a wh... more The facility layout problems in today's batch-to-mass manufacturing systems have gained a whole new face and popularity due to the requirements of mass customization. Facilities layout problem is still the most popular application for the Quadratic Assignment Problem [1]. The facility ...
Proceedings of the first ACM/SIGEVO Summit on Genetic and Evolutionary Computation - GEC '09, 2009
Multi-robot coverage path planning problems require every point in a given area to be covered by ... more Multi-robot coverage path planning problems require every point in a given area to be covered by at least one member of the robot team using their sensors. For a time-efficient coverage, the environment needs to be partitioned among robots in a balanced manner. So the problem ...
2009 IEEE International Conference on Control Applications, 2009
Abstract Minimizing the coverage task time is important for many sensor-based coverage applicati... more Abstract Minimizing the coverage task time is important for many sensor-based coverage applications. The completion time of a sensor-based coverage task is determined by the maximum time traveled by a robot in a mobile robot group. So the environment needs to be ...
Lecture Notes in Computer Science, 2009
Sensor-based mobile robot coverage path planning (MRCPP) problem is a challenging problem in robo... more Sensor-based mobile robot coverage path planning (MRCPP) problem is a challenging problem in robotic management. We here develop a genetic algorithm (GA) for MRCPP problems. The area subject to coverage is modeled with disks representing the range of sensing devices. Then the problem is defined as finding a path which runs through the center of each disk at least once with minimal cost of full coverage. The proposed GA utilizes prioritized neighborhood-disk information to generate practical and high-quality paths for the mobile robot. Prioritized movement patterns are designed to generate efficient rectilinear coverage paths with no narrow-angle turn; they enable GA to find optimal or near-optimal solutions. The results of GA are compared with a well-known approach called backtracking spiral algorithm (BSA). Experiments are also carried out using P3-DX mobile robots in the laboratory environment.
Robotics and Computer-Integrated Manufacturing, 2004
The high investment cost of flexible manufacturing systems (FMS) requires their management to be ... more The high investment cost of flexible manufacturing systems (FMS) requires their management to be effective and efficient. The effectiveness in managing FMSs includes addressing machine loading, scheduling parts and dispatching vehicles and the quality of the solution. Therefore the problem is inevitably multi-criteria, and decision maker's judgement may contribute to the quality of the solution and the systems's performance. On the other hand, each of these problems of FMS is hard to optimize due to the large and discrete solution spaces (NP-hard). The FMS manager must address each of these problems hierarchically (separately) or simultaneously (aggregately) in a limited time. The efficiency of the management is related to the response time.Here we propose a decision support system that utilizes an evolutionary algorithm (EA) with a memory of “good” past experiments as the solution engine. Therefore, even in the absence of an expert decision maker the performance of the solution engine and/or the quality of the solutions are maintained.The experiences of the decision maker(s) are collected in a database (i.e., memory-base) that contains problem characteristics, the modeling parameters of the evolutionary program, and the quality of the solution. The solution engine in the decision support system utilizes the information contained in the memory-base in solving the current problem. The initial population is created based on a memory-based seeding algorithm that incorporates information extracted from the quality solutions available in the database. Therefore, the performance of the engine is designed to improve following each use gradually. The comparisons obtained over a set of randomly generated test problems indicate that EAs with the proposed memory-based seeding perform well. Consequently, the proposed DSS improves not only the effectiveness (better solution) but also the efficiency (shorter response time) of the decision maker(s).
Journal of Statistical Computation and Simulation, 2007
In this study, we examine the genetic algorithms (GAs) for parameter estimation of nonlinear regr... more In this study, we examine the genetic algorithms (GAs) for parameter estimation of nonlinear regression models over a large set of test problems with three difficulty levels. A GA is developed based on a full-factorial experimental design. The proposed GA performs well for the test ...
This study deals with the problem of air transportation in Turkish Air Force. The Turkish Air For... more This study deals with the problem of air transportation in Turkish Air Force. The Turkish Air Force has different cargo aircraft to be used in air transportation operations, located in different airbases. The cargo aircraft are loaded cargo, equipment, personnel, repaired items etc. from one of airbases and transport them to the demanding airbases. In this military flight network, each airbase is a demand and support point for different kinds of items. Pickup and delivery demands are known deterministically. There are several operational constraints. The objective of the problem is to find a feasible set of routes for the cargo aircraft so that all requests are serviced, and such that the overall cost is minimized. Problem in hand is modeled and solved as multi-commodity, multi depot and heterogeneous vehicle pickup and delivery problem.
Bu kaynak, Moodle'in 1.7-1.9 versiyonarina yoneliktir. Yeni versiyonu icin yazar veya bolumle... more Bu kaynak, Moodle'in 1.7-1.9 versiyonarina yoneliktir. Yeni versiyonu icin yazar veya bolumle gorusunuz.
Journal of Aeronautics and Space Technologies, 2011
The aircraft routing is the process of assigning each individual aircraft within each fleet to fl... more The aircraft routing is the process of assigning each individual aircraft within each fleet to flight legs. The Federal Aviation Rules require the maintenance of all the aircrafts after specified hours of period as mandatory. The minimum total maintenance cost is provided as a result of the lost flight time which is brought to minimum. The common policies in this business sector follow the practices the maintenance of an aircraft once in 3-4 days periodically. This policy minimizes the risk of grounding of aircraft in the cost of the lost flight hours. In this study, we propose a concurrent, mathematical modeling approach for daily flight route and maintenance scheduling based on recorded flight hours. The model has been solved using CPLEX/GAMS MILP Software. The proposed approach was applied to the daily flight route-maintenance schedule problems of the domestic flights of two companies.
The steelmaking process consists of two phases: primary steelmaking and finishing lines. The sche... more The steelmaking process consists of two phases: primary steelmaking and finishing lines. The scheduling of the continuous galvanizing lines (CGL) is regarded as the most difficult process among the finishing lines due to its multi-objective and highlyconstrained nature. In this paper, we present a multi-population parallel genetic algorithm (MPGA) with a new genetic representation called k nearest neighbor representation, and with a new communication operator for performing better communication between subpopulations in the scheduling of CGL. The developed MPGA consists of two phases. Phase one generates schedules from a primary work in process (WIP) inventory filtered according to the production campaign, campaign tonnage, priorities of planning department, and the due date information of each steel coil. If the final schedule includes the violations of some constraints, module two repairs these violations by using a secondary WIP inventory of steel coils. The developed scheduling ...
A dispatching policy can be defined as a set of condition-action (CA) rules in which changing job... more A dispatching policy can be defined as a set of condition-action (CA) rules in which changing job-shop circumstances (such as number of waiting jobs in queues, machine queue lengths in minutes or hours, overall system utilization, machine utilizations, material transport equipment utilizations, work-in-process, and the like) correspond to the condition part and the dispatching rules (shortest processing time first, earliest due date, modified due date, critical ratio, and the like) correspond to the action part. Having considered the fact that advanced manufacturing technologies can enable job shops to practice dispatching policies as efficient as dispatching rules, this paper introduces an intelligent scheduling system that can learn dispatching policies depending on the queue lengths of machines by using Pitts approach of genetics-based machine learning (GBML) for dynamic job shops. In our proposed intelligent scheduling system, the Pitts approach of GBML performs a matching betwe...
Journal of the Faculty of Engineering and Architecture of Gazi University
Thesis (Ph. D.)--University of South Florida, 1997. Includes bibliographical references (leaves 1... more Thesis (Ph. D.)--University of South Florida, 1997. Includes bibliographical references (leaves 187-193).
Türk Sivil Havacılık sektörü, 2002-2008 yılları arasında gelişen ekonomi ve havacılık alanındaki ... more Türk Sivil Havacılık sektörü, 2002-2008 yılları arasında gelişen ekonomi ve havacılık alanındaki bazı kısıtlamaların kaldırılmasıyla % 53 oranında büyümüştür. Havayolu sektöründe başarılı uluslararası firmalar planlama ve çizelgeleme problemlerini çözmede gelişmiş bilgisayar-destekli çözüm yöntemleri kullanmaktadır. Bu yöntemler işletmelere ciddi rekabet üstünlüğü sağlamaktadır. Havayolu sektöründe dört temel operasyonel planlama ve çizelgeleme problemi bulunmaktadır: uçuş çizelgeleme, uçak çizelgeleme, ekip çizelgeleme ve düzensiz olayların yönetimi. Tüm havayolu işletmelerinin karşı karşıya kaldığı söz konusu operasyonel planlama ve çizelgeleme problemleri bu çalışmada ayrıntılı olarak incelenmiştir. İncelemeler, işletmelerin söz konusu yöntemleri kullanarak maliyetlerinde önemli kazanımlar sağladığını ortaya koymaktadır. Bununla birlikte, büyük ölçekli problemlerin çözümü için gereken süre karar vericilerin arzu ettikleri karar kalitesini tatmin etmeyebilmektedir. Böylesi durumlarda gelişmiş teknolojilerle bütünleştirilmiş modern karar yöntemlerinin kullanılması da işletmelere ciddi maliyet üstünlüğü fırsatı sunmaktadır.
Batch Processing Systems Engineering, 1996
This paper introduces a multi -population genetic algorithm (M-PPGA) using a new genetic represen... more This paper introduces a multi -population genetic algorithm (M-PPGA) using a new genetic representation, the kth-nearest neighbor representation, for Euclidean Traveling Salesman Problems. The proposed M-PPGA runs M g reedy genetic algorithms on M separate populations, each with two new operators, intersection repairing and cheapest insert. The M-PPGA finds optimal or near optimal solutions by using a novel communication operator
Lecture Notes in Computer Science, 2006
Abstract. The steelmaking process consists of two phases: primary steelmaking and finishing lines... more Abstract. The steelmaking process consists of two phases: primary steelmaking and finishing lines. The scheduling of the continuous galvanizing lines (CGL) is regarded as the most difficult process among the finishing lines due to its multi-objective and highly-constrained nature. ...
Lecture Notes in Computer Science, 2006
The facility layout problems in today's batch-to-mass manufacturing systems have gained a wh... more The facility layout problems in today's batch-to-mass manufacturing systems have gained a whole new face and popularity due to the requirements of mass customization. Facilities layout problem is still the most popular application for the Quadratic Assignment Problem [1]. The facility ...
Proceedings of the first ACM/SIGEVO Summit on Genetic and Evolutionary Computation - GEC '09, 2009
Multi-robot coverage path planning problems require every point in a given area to be covered by ... more Multi-robot coverage path planning problems require every point in a given area to be covered by at least one member of the robot team using their sensors. For a time-efficient coverage, the environment needs to be partitioned among robots in a balanced manner. So the problem ...
2009 IEEE International Conference on Control Applications, 2009
Abstract Minimizing the coverage task time is important for many sensor-based coverage applicati... more Abstract Minimizing the coverage task time is important for many sensor-based coverage applications. The completion time of a sensor-based coverage task is determined by the maximum time traveled by a robot in a mobile robot group. So the environment needs to be ...
Lecture Notes in Computer Science, 2009
Sensor-based mobile robot coverage path planning (MRCPP) problem is a challenging problem in robo... more Sensor-based mobile robot coverage path planning (MRCPP) problem is a challenging problem in robotic management. We here develop a genetic algorithm (GA) for MRCPP problems. The area subject to coverage is modeled with disks representing the range of sensing devices. Then the problem is defined as finding a path which runs through the center of each disk at least once with minimal cost of full coverage. The proposed GA utilizes prioritized neighborhood-disk information to generate practical and high-quality paths for the mobile robot. Prioritized movement patterns are designed to generate efficient rectilinear coverage paths with no narrow-angle turn; they enable GA to find optimal or near-optimal solutions. The results of GA are compared with a well-known approach called backtracking spiral algorithm (BSA). Experiments are also carried out using P3-DX mobile robots in the laboratory environment.
Robotics and Computer-Integrated Manufacturing, 2004
The high investment cost of flexible manufacturing systems (FMS) requires their management to be ... more The high investment cost of flexible manufacturing systems (FMS) requires their management to be effective and efficient. The effectiveness in managing FMSs includes addressing machine loading, scheduling parts and dispatching vehicles and the quality of the solution. Therefore the problem is inevitably multi-criteria, and decision maker's judgement may contribute to the quality of the solution and the systems's performance. On the other hand, each of these problems of FMS is hard to optimize due to the large and discrete solution spaces (NP-hard). The FMS manager must address each of these problems hierarchically (separately) or simultaneously (aggregately) in a limited time. The efficiency of the management is related to the response time.Here we propose a decision support system that utilizes an evolutionary algorithm (EA) with a memory of “good” past experiments as the solution engine. Therefore, even in the absence of an expert decision maker the performance of the solution engine and/or the quality of the solutions are maintained.The experiences of the decision maker(s) are collected in a database (i.e., memory-base) that contains problem characteristics, the modeling parameters of the evolutionary program, and the quality of the solution. The solution engine in the decision support system utilizes the information contained in the memory-base in solving the current problem. The initial population is created based on a memory-based seeding algorithm that incorporates information extracted from the quality solutions available in the database. Therefore, the performance of the engine is designed to improve following each use gradually. The comparisons obtained over a set of randomly generated test problems indicate that EAs with the proposed memory-based seeding perform well. Consequently, the proposed DSS improves not only the effectiveness (better solution) but also the efficiency (shorter response time) of the decision maker(s).
Journal of Statistical Computation and Simulation, 2007
In this study, we examine the genetic algorithms (GAs) for parameter estimation of nonlinear regr... more In this study, we examine the genetic algorithms (GAs) for parameter estimation of nonlinear regression models over a large set of test problems with three difficulty levels. A GA is developed based on a full-factorial experimental design. The proposed GA performs well for the test ...