Browsing by Author "Subulan, Kemal"

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Capability-Based Machine Layout With a Matheuristic-Based Approach
(Pergamon-elsevier Science Ltd, 2022) Baykasoglu, Adil; Subulan, Kemal; Hamzadayi, Alper
Capability-based machine layout (CB-ML) problem is firstly introduced in this paper. In the conventional ma-chine layout problem, part flow matrix is generated from parts' machine routes to minimize total part flows. However, defining part flow matrix based on the machines' routes (instead of processing capability requirements of parts) restricts facility designers to utilize available flexibility in manufacturing systems. In this research, parts' processing requirements are defined in terms of Resource Elements (REs), which describe unique pro-cessing capabilities and the processing capability overlaps of machines. If part flow matrix is defined in terms of REs, it becomes possible to utilize available flexibility in a more effective manner. However, physical part flows cannot be identified directly from the RE-based flow matrices. Because, the processing requirements of manu-factured parts can be satisfied from alternative machines that contain the required REs. Therefore, RE-based part flow matrix must be mapped into the machine flow matrix, which requires defining the machine flow matrix as a decision variable. This makes the proposed CB-ML problem much more complicated than the conventional machine layout problem. We firstly developed an integer non-linear programming model for the proposed CB-ML problem. Because of its NP-completeness and nonlinear structure, a matheuristic-based solution approach is also developed. The extensive computational analysis have shown that the proposed approach is able to provide good quality solutions for the larger problem instances within reasonable computation times.
A Comparative Study of Modeling and Solution Approaches for the Multi-Mode Resource-Constrained Discrete Time-Cost Trade-Off Problem: Case Study of an Erp Implementation Project
(Pergamon-elsevier Science Ltd, 2022) Cakir, Gizem; Subulan, Kemal; Yildiz, Seyda Topaloglu; Hamzadayi, Alper; Asilkefeli, Ceren
Most knowledge-intensive industries, especially companies developing software engineering projects such as Enterprise Resource Planning (ERP) implementation projects, generally necessitate finding the optimal trade-off between the project duration and total usage cost of the renewable resource costs (e.g., human resource expertise costs). Therefore, the MRC-DTCTP, which integrates classical multi-mode resource-constrained project scheduling (MRCPSP) and discrete time-cost trade-off problems (DTCTP), can be seen as a more applicable problem since it better reflects the objectives and requirements of today's real-life software project applications. The MRC-DTCTP is a much more complex variant of the MRCPSP since it aims to minimize total direct/indirect costs of the resources simultaneously under a pre-specified project deadline. Based on this motivation, a new explicit integer-linear programming (ILP) model of the MRC-DTCTP was first developed based on the implicit non-linear programming model of Wuliang and Chengen (2009). Due to its NP-hard nature, we also proposed a constraint programming (CP) model that includes several search strategies to solve large-sized problem instances within reasonable computation time. In addition, a genetic algorithm (GA) approach in combination with a Modified Serial Schedule Generation scheme (SSGS) is implemented to make further comparisons on several benchmark instances, which are generated based on the existing MRCPSP data sets taken from the project scheduling problem library (PSPLIB) by considering additional problem characteristics. A comprehensive experimental study has shown that the proposed CP model and GA approach can provide superior results in shorter run times for large-sized benchmark instances. Finally, an international Enterprise Resource Planning (ERP) Software Company's real-life application is presented. The ERP projects generally necessitate finding the optimal trade-off between project makespan and human resource costs, making the MRC-DTCTP much more difficult than classical MRCPSPs & DTCTPs. For further analysis, time-cost trade-off curves under different human resource avail abilities and project deadlines are drawn to provide managerial insights to ERP project managers.
Great Deluge-Based Metaheuristic Incorporating Integer Nonlinear Programming for Modeling and Solving Dynamic Capability-Based Machine Layout Problem
(Pergamon-Elsevier Science Ltd, 2026) Baykasoglu, Adil; Subulan, Kemal; Hamzadayi, Alper
This paper introduces a novel Dynamic Capability-Based Machine Layout (DCB-ML) problem by integrating the Quadratic Assignment Problem (QAP) formulation with a Dynamic Capability-Based Part Flow Assignment (DCB-PFA) problem. This integration enables the simultaneous consideration of machines' processing capabilities, routing flexibility, dynamic flow assignment, and machine capacity utilization. First, a new Integer Nonlinear Programming (INLP) model is developed. The dynamic part flows are determined via the DCB-PFA sub-problem, while machine-location assignments are obtained by solving QAP. To address the complex nature of this problem, a hybrid solution approach is proposed that combines a Great Deluge Algorithm (GDA) with a Mixed-Integer Linear Programming (MILP) model, complemented by local search procedures. Since the problem has a decomposable structure, the proposed approach allows each sub-problem to be addressed independently, while the overall solution quality is jointly evaluated. Decomposition reduces the size of the resulting MILP model, as several binary variables and assignment constraints are eliminated. The proposed hybrid approach is also compared with the INLP and its linearized equivalent on several test problems. For large-scale problems with medium to high capability overlaps, nonlinear and MIP solvers fail to obtain feasible solutions, whereas the proposed approach can efficiently generate high-quality solutions within reasonable times. Moreover, when the effects of different machine-capability overlaps are investigated, it is observed that the solution of the problem will be more complex in the case of higher machine-capability overlaps. However, considering machine capabilities improves overall layout scores and eliminates the necessity of frequent reconfigurations, which is costly and time-consuming.