Mühendislik Fakültesi / Faculty of Engineering
Permanent URI for this collectionhttps://hdl.handle.net/11727/1401
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Item Heterogeneous Vehicle Routing Problem with Simultaneous Pickup and Delivery: Mathematical Formulations and A Heuristic Algorithm(2015) Kececi, Baris; Altiparmak, Fulya; Kara, Imdat; 0000-0002-2730-5993; AAF-7020-2021; AAC-4793-2019; ABH-1078-2021; F-1639-2011One of the most important operational decisions in the logistics management is to determine the vehicle routes serving the customers. The Vehicle Routing Problem (VRP) can be defined as the determination of the optimal routes which meet the delivery (or pickup) demands from the depot to the customers. In the real life applications of logistics, vehicles in a fleet may differ from each other. In addition, the requirements arising from customers/goods may reveal the necessity to use different vehicles. Besides, companies do care more about the management of reverse flow of products, semi-finished and raw materials because of their economic benefits and as well as legal and environmental liabilities. In this paper, a variant of the VRP is considered with heterogeneous fleet of vehicles and simultaneous pickup and delivery. This problem is referred to Heterogeneous Vehicle Routing Problem with Simultaneous Pickup and Delivery (HVRPSPD). The HVRPSPD can be defined as determining the routes and the vehicle types on each route while minimizing the total cost. In this paper, a polynomial sized flow-based mathematical model is proposed for the HVRPSPD. Since the HVRPSPD is in the class of NP-hard problems, it is difficult to find the optimal solution in a reasonable time even for the moderate size problems. Therefore, a simple and constructive heuristic algorithm is proposed to solve the medium and large scale HVRPSPD s. This algorithm is the adaptation of very well-known Clarke-Wright Savings approach, which has originally developed for the VRP, to the HVRPSPD. The performances of the proposed mathematical model and the heuristic algorithm have been examined on the test problems.Item New Formulations for The Traveling Repairman Problem with Time Windows(2018) Kara, Imdat; Uzun, Gozde Onder; ABH-1078-2021Item An Integrated Fuzzy TOPSIS-Knapsack Problem Model for Order Selection in a Bakery(2017) Ic, Yusuf Tansel; Ozel, Melis; Kara, Imdat; 0000-0001-9274-7467; AGE-3003-2022; ABH-1078-2021In this study, a new model has been developed for the order selection problem for a bakery firm located in Turkey. We consider a combined order selection and process planning problem where a make-to-order bakery goods producer firm has to determine a set of orders to process so as to maximize the total profit. The developed model combines setup costs, sales price, lot size, demand and other important daily data of the products. After collecting the related data, fuzzy TOPSIS method is used to obtain the rankings of the orders (bread types). Then, the ranking scores are incorporated in the knapsack problem to determine the lot size and which orders to select. A computer application is also provided in the paper. With the help of MS Excel Visual Basic program, the computer application updates data daily, ranks the products, determines the lot size, and helps the decision maker with the selection of orders. The computational results show that the proposed method presented better results than the current method applied in the firm. Comparing the two methods in terms of cost reduction, the proposed method gives better results than the current method with 27%. Furthermore, the proposed computer program does not need extra special software or a commercial computer program, which is favorable for small-size enterprises.Item The Location-Routing Problem with Simultaneous Pickup and Delivery: Formulations and A Heuristic Approach(2012) Karaoglan, Ismail; Altiparmak, Fulya; Kara, Imdat; Dengiz, Berna; 0000-0002-6023-6918; 0000-0003-1730-4214; AAG-4982-2019; AAF-7020-2021; ABH-1078-2021In this paper, we consider a variant of the Location-Routing Problem (LRP), namely the LRP with simultaneous pickup and delivery (LRPSPD). The LRPSPD seeks to minimize total cost by simultaneously locating the depots and designing the vehicle routes that satisfy pickup and delivery demand of each customer at the same time. We propose two polynomial-size mixed integer linear programming formulations for the problem and a family of valid inequalities to strengthen the formulations. While the first formulation is a node-based formulation, the second one is a flow-based formulation. Furthermore, we propose a two-phase heuristic approach based on simulated annealing, tp_SA, to solve the large-size LRPSPD and two initialization heuristics to generate an initial solution for the tp_SA. We then empirically evaluate the strengths of the proposed formulations with respect to their ability to find optimal solutions or strong lower bounds, and investigate the performance of the proposed heuristic approach. Computational results show that the flow-based formulation performs better than the node-based formulation in terms of the solution quality and the computation time on small-size problems. However, the node-based formulation can yield competitive lower bounds in a reasonable amount of time on medium-size problems. Meantime, the proposed heuristic approach is computationally efficient in finding good quality solutions for the LRPSPD. (C) 2011 Elsevier Ltd. All rights reserved.Item New Integer Linear Programming Formulation for the Traveling Salesman Problem with Time Windows: Minimizing Tour Duration with Waiting Times(2013) Kara, Imdat; Koc, Ozge Nimet; Altiparmak, Fulya; Dengiz, Berna; 0000-0003-1730-4214; ABH-1078-2021; ABH-1078-2021The travelling salesman problem, being one of the most attractive and well-studied combinatorial optimization problems, has many variants, one of which is called travelling salesman problem with Time Windows (TSPTW)'. In this problem, each city (nodes, customers) must be visited within a time window defined by the earliest and the latest time. In TSPTW, the traveller has to wait at a city if he/she arrives early; thus waiting times directly affect the duration of a tour. It would be useful to develop a new model solvable by any optimizer directly. In this paper, we propose a new integer linear programming formulation having O(n(2)) binary variables and O(n(2)) constraints, where (n) equals the number of nodes of the underlying graph. The objective function is stated to minimize the total travel time plus the total waiting time. A computational comparison is made on a suite of test problems with 20 and 40 nodes. The performances of the proposed and existing formulations are analysed with respect to linear programming relaxations and the CPU times. The new formulation considerably outperforms the existing one with respect to both the performance criteria. Adaptation of our formulation to the multi-traveller case and some additional restrictions for special situations are illustrated.Item A Systematic Approach to Reduce Human and System-related Errors Causing Customer Dissatisfaction in a Production Environment(2009) Pakdil, Fatma; Oezkoek, Onur; Dengiz, Berna; Kara, Imdat; Selvi, Nilay; Karg, Alper; ABH-1078-2021In this study, a systematic methodology for business process improvement, which aims to eliminate human and system-related errors resulting in customer dissatisfaction in a production environment, is presented. The proposed methodology consists of problem identification and analysis, preventing human-related errors and system-related error steps respectively. The methodology was also implemented in a real-life organisation. Current and proposed systems are compared via a simulation model to examine the results of process improvements. The case study shows that the proposed methodology works exceedingly well and yields considerable improvement in the process under study. The most important and impressive difference of this paper from the previous literature is that process improvement needs are derived directly from customer dissatisfaction reasons and solved by the proposed systematic methodology. In this way human-related and system-related errors were perceived opportunities for improvement.Item Traveling Repairmen Problem: A Biogeography-Based Optimization(2022) Uzun, Gozde Onder; Dengiz, Berna; Kara, Imdat; Karasan, Oya EkinTraveling Repairman Problem (TRP), which is also known by names cumulative traveling salesman problem, the deliveryman problem and the minimum latency problem, is a special variant of Traveling Salesman Problem (TSP). In contrast to the minimization of completion time objective of TSP, the desired objective of TRP is to minimize the cumulative latency (waiting time or delay time) of all customers. In this paper, a generalized version of TRP with multi depots and time windows, namely Multi Depot Traveling Repairman Problem with Time Windows (MDTRPTW) is considered. A group of homogeneous repairmen initiate and finish their visit tours at multiple depots. Each customer must be visited exactly by one repairman within their provided earliest end latest times. Being a challenging Nondeterministic Polynomial-hard (NP-hard) optimization problem, exact solution approaches are not expected to scale to realistic dimensions of MDTRPTW. Thus, we propose a biogeography-based optimization algorithm (BBOA) as a metaheuristic approach to solve large size MDTRPTW problems. The proposed metaheuristic is analyzed in terms of solution quality, coefficient of variation as well as computation time by solving some test problems adapted from the related literature. The efficacy of the proposed solution methodology is demonstrated by solving instances with 288 customers within seconds.Item New formulations for multiple traveler minimum latency problem with time windows(2022) Uzun, Gozde Onder; Kara, Imdat; ABH-1078-2021In this paper, new mathematical models for homogeneous and heterogeneous multiple traveler minimum latency problem with time windows (kLPTW), named as M2 and M4 are developed. These models are computationally compared with existing models named as M1 and M3 for kLPTW in terms of CPU times and percentage deviation from linear programming relaxation values. A short summary of the computational analysis is given in table A below. In Table A, k is the number of travelers. The first column under the number of traveler cell shows the average CPU times of problems solved in time limit and the second column shows the average percentage deviations. We observed that, our formulations are superior than the existing formulations for all the problems for both kLPTW types with respect to each performance criteria. Purpose: The aim of this study is to develop new mathematical formulations for homogeneous and heterogeneous multiple traveler minimum latency problem with time windows. Theory and Methods: Based on the mixed integer linear programming, mathematical models with polynomial number of decision variables and constraints are developed. Benchmark instances from the literature are solved with existing formulations and proposed new formulations by using CPLEX 12.5.0.1. CPU times and percentage deviation from linear programming relaxation values are considered as performance criteria. Results: We solved 125 problems with varying number of nodes and time windows. In all the problem solved proposed formulations are better than the existing formulations in terms of both of the performance criteria. Conclusion: The proposed formulations for homogeneous and heterogeneous multiple traveler minimum latency problem with time windows are superior than the existing formulations and able to solve the problems up to 100 nodes with narrow time windows. Proposed formulations may be used to solve small and moderate real-life problems very easily. They may also be used for testing the performance of the heuristics constructed for kLPTW.Item A multiobjective mathematical model to form the best team at sports clubs: team harmony and player performance objectives(2022) Budak, Gercek; Kara, ImdatPurpose Team coaches of sports clubs are highly concerned when forming the best team to win the upcoming match at the stage before that particular game. Even if a team squad is comprising of a limited number of players, the combination of them makes a complicated problem with a huge number of possible line-ups. This study aims to build a mathematical model to solve this problem with the objectives of maximum player performance and team harmony. Design/methodology/approach This paper proposes a novel approach of a multiobjective mathematical model on team harmony and player performance. Two objectives are chosen as these are the most important perspectives that define the best team. The model outputs are nondominated solutions of these two objectives. Findings These solutions are displayed to the team coach to decide the best team according to strategical, psychological and conditional preferences of him/her. A real-life example is demonstrated to show the model validity and interpretation of the results by using the technique for order preference by similarity to an ideal solution on a volleyball team formation problem. Originality/value This paper proposes a multiobjective mathematical model on team harmony and player performance to solve the team coach's hard and complicated problem.Item A Mathematical Formulation And Heuristic Approach For The Heterogeneous Fixed Fleet Vehicle Routing Problem With Simultaneous Pickup And Delivery(2021) Kececi, Baris; Altiparmak, Fulya; Kara, Imdat; ABH-1078-2021This study considers a variant of the vehicle routing problem (VRP) called the heterogeneous VRP with simultaneous pickup and delivery (HVRPSPD). The HVRPSPD may broadly be defined as identifying the minimum cost routes and vehicle types. To solve the HVRPSPD, first, we propose a polynomial-size mixed integer programming formulation. Because the HVRPSPD is an NP-hard problem, it is difficult to determine the optimal solution in a reasonable time for moderate and large-size problem instances. Hence, we develop a hybrid metaheuristic approach based on the simulated annealing and local search algorithms called SA-LS. We conduct a computational study in three stages. First, the performance of the mathematical model and SA-LS are investigated on small and medium-size HVRPSPD instances. Second, we compare SA-LS with the constructive heuristics, nearest neigh-borhood and Clarke-Wright savings algorithms, adapted for the HVRPSPD. Finally, the performance of SA-LS is evaluated on the instances of the heterogeneous VRP (HVRP), which is a special case of the HVRPSPD. Computational results demonstrate that the mathematical model can solve small-size instances optimally up to 35 nodes; SA-LS provides good quality solutions for medium and large-size problems. Moreover, SA-LS is superior to simple constructive heuristics and can be a preferable solution method to solve HVRP and VRPSPD instances successfully.