Cevriye Gencer

A Method Based on SMAA-Topsis for Stochastic Multi-Criteria Decision Making and a Real-World Application

Stochastic multi-criteria acceptability analysis (SMAA-2) and the technique for order preference by similarity to ideal solution (TOPSIS) are methods for evaluating alternatives with multiple criteria. SMAA is a method that is used for solving multi-criteria decision-making problems with uncertain, inaccurate information, and does not require preference information from the decision makers. The TOPSIS method is based on the principle of determining a solution with the shortest distance to the ideal solution and the greatest distance from the negative-ideal solution. This paper proposes a new method, SMAA-TOPSIS, by combining the SMAA and TOPSIS methods. The SMAA-TOPSIS method was executed for two problems: drug benefit-risk analysis and machine gun selection. This paper found that TOPSIS could be used with uncertain and arbitrarily distributed values for weights and criteria measurements by using a combination of SMAA and TOPSIS. Also, we obtained clearer and consistent SMAA outputs.

A new intuitional algorithm for solving heterogeneous fixed fleet routing problems: Passenger pickup algorithm

Fixed-fleet heterogeneous vehicle routing is a type of vehicle routing problem that aims to provide service to a specific customer group with minimum cost, with a limited number of vehicles with different capacities. In this study, a new intuitional algorithm, which can divide the demands at the stops for fixed heterogeneous vehicle routing, is developed and tested on tests samples. The algorithm is compared to the BATA Algorithm available in the literature in relation to the number of vehicles, fixed cost, variable cost and total cost.

A decision support system for locating weapon and radar positions in stationary point air defence

In this study, a decision support system (DSS) based on the interactive use of location models and geographical information systems (GIS) was developed to determine the optimal positions for air defence weapons and radars. In the location model, the fire units are considered as the facilities to be located and the possible approach routes of air vehicles are treated as demand points. Considering the probability that fire by the units will miss the targets, the objective of the problem is to determine the positions that provide coverage of the approach routes of the maximum number of weapons while considering the military principles regarding the tactical use and deployment of units. In comparison with the conventional method, the proposed methodology presents a more reliable, faster, and more efficient solution. On the other hand, owing to the DSS, a battery commander who is responsible for air defence becomes capable of determining the optimal weapon and radar positions, among the alternative ones he has identified, that cover the possible approach routes maximally. Additionally, he attains the capability of making such decisions in a very short time without going to the field over which he will perform the defence and hence without being subject to enemy threats. In the decision support system, the digital elevation model is analysed using Map Objects 2.0, the mathematical model is solved using LINGO 4.0 optimization software, and the user interface and data transfer are supported by Visual Basic 6.0.

Chemical agent detector placement methodology

Abstract Terrorism is a threat to global peace in our world today and in the future this terrorist threat is surely going to be important. Global terrorist groups have highly sophisticated weapon systems with them to terrorize the humanity. Asymmetric warfare which is accepted especially by rough states against free nations is also a threat to humanity. It includes terrorism, weapons of mass destruction, electronic and information war. In this concept, nuclear, biological and chemical (NBC) weapons are the most preferred ones in asymmetric warfare strategy because of their special characteristics. According to this strategy; cities, urban territories, critical military and civilian facilities are the main targets of terrorist attacks. In many developing countries, military zones which were located out of cities at first, happened to be surrounded by urban territories. This situation made the military zones more vulnerable to attacks by terrorists hiding amongst civilians. Another reason for military zones to be a possible target for attacks is the great terror on civilians which will be probably caused by such an attack. In this kind of sensational attacks, chemical agents and chemical weapons will be probably used because of their characteristics. This analytical research is done because key military zones mentioned above must be defensed against these kinds of attacks. While formulating the problem, to find the best locations for the point and the line of sight detectors which are used to identify chemical hazard and warn friendly forces about approaching danger, two models are structured and proposed on the basis of The Maximal Covering and The Maximal Expected Covering Models. In the proposed models, the optimum locations for detectors and alarms are found and the best matching between these detectors and alarms is given. In this research, for a threat point to be covered by a detector, that point must be in the detection range and an alarm must be linked to that detector. Additionally, for the line of the sight detection systems, a threat point must be in the line of sight of detectors. According to the method of this research, chemical defence systems are tried to be optimally set in key military zones during peace time well before attacks. With the proposed models, a solution and an analysis are done in a selected military zone as an example and that zone is tried to be defensed against a possible chemical terrorist attack.

Mining classification rules with Reduced MEPAR-miner Algorithm

Abstract In this study, a new classification technique based on rough set theory and MEPAR-miner algorithm for association rule mining is introduced. Proposed method is called as ‘Reduced MEPAR-miner Algorithm’. In the method being improved rough sets are used in the preprocessing stage in order to reduce the dimensionality of the feature space and improved MEPAR-miner algorithms are then used to extract the classification rules. Besides, a new and an effective default class structure is also defined in this proposed method. Integrating rough set theory and improved MEPAR-miner algorithm, an effective rule mining structure is acquired. The effectiveness of our approach is tested on eight publicly available binary and n -ary classification data sets. Comprehensive experiments are performed to demonstrate that Reduced MEPAR-miner Algorithm can discover effective classification rules which are as good as (or better) the other classification algorithms. These promising results show that the rough set approach is a useful tool for preprocessing of data for improved MEPAR-miner algorithm.

A combined approach for fuzzy multi-objective multiple knapsack problems for defence project selection

In this study, a model representing military requirements as scenarios and capabilities is offered. Pair-wise comparisons of scenarios are made according to occurrence probabilities by using the Analytical Hierarchy Process (AHP). The weights calculated from AHP are used as the starting weights in a Quality Function Deployment (QFD) matrix. QFD is used to transfer war fighter requirements into the benefit values of projects. Two levels of QFD matrices are used to evaluate new capability areas versus capabilities and capabilities versus projects. The benefit values of the projects are used in a multi-objective problem (multi-objective multiple knapsack problem) that considers the project benefit, implementation risks and environmental impact as multiple objectives. Implementation risk and environmental impact values are also calculated using the same combined AHP and QFD methodology. Finally, the results of the fuzzy multi-objective goal programming suggest a list of projects that offers optimal benefit when carried out within multiple budgets.

A decision support system for locating VHF/UHF radio jammer systems on the terrain

In this study, a mathematical model is suggested concerning the location of VHF/UHF frequency radio jammer systems to the terrain parts to conduct single frequency or sequential frequency jamming, and then a decision support system (DSS), based on the suggested model, is formed. Location problem is modelled by the maximum covering location problem and LINGO-8 package program is used to solve the model. Interaction with the user is provided via the MS-Excel program in the DSS. In the application part of the study, a scenario was set up and the model was run for the two cases, weighted and equally weighted situations of the targets. With the same scenario, backup positions for the jammer systems were tried to be determined and solutions for the scenario were evaluated.

A decision network algorithm for multi-stage dynamic lot sizing problems

In this note, a new solution procedure similar to critical path analysis in network theory is developed for determining dynamic uncapacitated lot sizing in multi-stage production systems. The algorithm offered is a Decision Network Algorithm. An example is given to illustrate the algorithm.

Dinamik İnsansız Hava Sistemleri Rota Planlaması Literatür Araştırması ve İnsansız Hava Araçları Çalışma Alanları

İnsansız Hava Sistemleri (İHS) ile sağlanan teknolojik olanaklar kadar önemli olan bir husus da, kullanıcının bu olanakları etkin şekilde planlayabilmesi, ihtiyacı olan anlık değişikliğe çabuk ayak uydurabilmesi, karar vericiler için önemli olabilecek bilgiyi doğru ve zamanında paylaşabilmesi, kısaca ağ üzerinde verimli çalışabilmesidir. Muhabere Elektronik ve Bilgi Sistemleri (MEBS)’ndeki gelişmeler, Araç Rotalama Probleminin (ARP) dinamik durumlarda da çözümünü mümkün kılmıştır. Bu bağlamda İHS’lerinin, keşif faaliyetleri rota planlanması kapsamındaki ARP uygulamaları her geçen gün gelişerek artmaktadır. Bu makalenin amacı, İHS’lerinin “dinamik rota planlaması” kapsamında yapılan literatür çalışmalarının incelenmesi, kapsamlarının tespiti, bu alandaki gelişmeler ile çalışılmayan alanların belirlenmesi ve böylelikle ileride araştırma yapılabilecek alanlara yön verilmesidir. Bu sayede, İHS’lerin havada kalış süresinin artırılmasından ziyade, havada kaldığı müddetçe yol için ayrılan “niteliksiz” zamanın azaltılarak, hedefler üzerindeki görevini icra ettiği “nitelikli” zamanın artırılması hedeflenmektedir. Outwith the technological developments made with Unmanned Aerial Vehicles (UAV); other important issues for the users like effective planning and re-planning; providing the clear, concise and timely information to the decision makers is part of the Network Enabled Capability. Significant improvements to the Communication and Information systems have made it possible to find dynamic solutions for Vehicle Routing Problems. In this context, “Vehicle Routing” applications for UAVs in reconnaissance missions are increasing exponentially. This study investigates the literature in “dynamic route planning”, defining the scope and identifying shortcomings for future studies in Unmanned Aerial Systems. Using this approach not only reduces stagnant travel time to target time but increases the usable times spent on targets.

Simultaneous Pick-up and Delivery Decision Support Systems

The problems concerning the distribution of goods between depots and final users are known as Vehicle Routing Problems (VRP). Dantzig & Ramser (1959) introduced VRP. The authors described a real world application and proposed the first mathematical programming formulation and algorithmic approach for the solution of the problem. Let G= (V, A) is a graph where { } 0 1 , , n V v v v = A is a vertex set and