Endüstri Mühendisliği Bölümü Yayın Koleksiyonu

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  • Article
    Citation - Scopus: 4
    Scheduling With Lot Streaming in a Two-Machine Re-Entrant Flow Shop
    (Regional Association for Security and crisis management, 2021) Duman, M.; Çetinkaya, F.C.
    Lot streaming is splitting a job-lot of identical items into several sublots (portions of a lot) that can be moved to the next machines upon completion so that operations on successive machines can be overlapped; hence, the overall performance of a multi-stage manufacturing environment can be improved. In this study, we consider a scheduling problem with lot streaming in a two-machine re-entrant flow shop in which each job-lot is processed first on Machine 1, then goes to Machine 2 for its second operation before it returns to the primary machine (either Machine 1 or Machine 2) for the third operation. For the two cases of the primary machine, both single-job and multi-job cases are studied independently. Optimal and near-optimal solution procedures are developed. Our objective is to minimize the makespan, which is the maximum completion time of the sublots and job lots in the single-job and multi-job cases, respectively. We prove that the single-job problem is optimally solved in polynomial-time regardless of whether the third operation is performed on Machine 1 or Machine 2. The multi-job problem is also optimally solvable in polynomial time when the third operation is performed on Machine 2. However, we prove that the multi-job problem is NP-hard when the third operation is performed on Machine 1. A global lower bound on the makespan and a simple heuristic algorithm are developed. Our computational experiment results reveal that our proposed heuristic algorithm provides optimal or near-optimal solutions in a very short time. © 2021 by the authors. Submitted for possible open access publication under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
  • Article
    Citation - WoS: 15
    Citation - Scopus: 22
    Intermodal Transportation in Humanitarian Logistics With an Application To a Turkish Network Using Retrospective Analysis
    (Elsevier, 2022) Akdogan, Muharrem Altan; Kahya, Melike; Ertem, Mustafa Alp
    In the event of disruptions in a transportation network following a disaster, humanitarian organizations find it challenging to provide basic requirements for beneficiaries. Demand may be met using intermodal transportation as an alternative when the unimodal transportation infrastructure is damaged. This study proposes a mathematical model for utilizing intermodal transportation using 40 ft standard containers while delivering relief supplies by road, rail, and sea modes. The proposed model is a capacitated multi-period multicommodity intermodal network flow model in which relief supplies are delivered to beneficiaries in three echelons (i.e., supply, intermodal hub, and demand). The Turkish Disaster and Emergency Management Presidency's container warehouses (i.e., supply), logistics centers and container ports (i.e., intermodal hubs) are utilized to test the mathematical model with real-life demand parameters. Retrospective analysis was performed to determine the most frequently used container warehouses, logistics centers, and origin-destination pairs. Hence, an increase in operational capacity and infrastructure reinforcement is recommended to mitigate the effects of future disasters. We found that intermodal transportation is more robust to network disruptions in rapidly delivering relief supplies. We observed that intermodal transportation is utilized in disasters with more than 50,000 beneficiaries or disrupted unimodal infrastructure. For instance, after the future Istanbul earthquake, it would be impossible to deliver the relief materials only by road transportation within the urgent response period. Thus, the benefits of intermodal transportation in humanitarian logistics are more visible in large-scale disasters in which transportation resources are scarce, and transportation infrastructure is more likely to be destroyed.
  • Article
    Citation - Scopus: 21
    Analysis of Barriers To the Adoption of Circular Supply Chain Management: a Case Study in the Air Conditioning Industry
    (Taylor and Francis Ltd., 2023) Çıkmak, S.; Kesici, B.
    Circular supply chain management (CSCM) is a process used to design the supply chain by recycling, remanufacturing or refurbishing, repairing, and reusing products However, no study has been encountered in the literature that analyzes CSCM barriers in the air conditioning sector. Hence, this study is aimed to investigate the barriers to CSCM adoption in the air conditioning industry. A case study was conducted on a company operating in the global air conditioning sector. Initially, literature review and expert opinions have been used to identify essential barriers. Later, 6 main barriers and 21 sub-barriers were ranked using Analytical Hierarchy Process (AHP) method based on the interval type-2 fuzzy sets. The findings indicate that “Regulatory” is the most crucial, and “Operational” is the least important main barrier. The findings of the study would be useful for practitioners and policymakers to focus on the most prominent barriers in the air conditioning supply chains. © 2023 Chinese Institute of Industrial Engineers.
  • Article
    Citation - Scopus: 23
    Using Announcement Options in the Bid Construction Phase for Disaster Relief Procurement
    (2012) Ertem, M.A.; Buyurgan, N.; Pohl, E.A.
    This paper presents an analysis of the bid construction phase of procurement auctions in disaster relief and humanitarian logistics. Substitution and partial fulfillment options are presented in formulations to allow bidders with fewer inventories to offer substitute item types and partial bids in auctions. During the auction announcement phase, a coordinating platform for disaster locations (i.e., auctioneer) allows substitution and partial fulfillment options to the relief suppliers (i.e., bidders) when acceptable. Thus, suppliers with fewer inventories can offer substitute item types and participate in more auctions by partially bidding. A genetic algorithm, a simulated annealing algorithm and an integer program are used for the analysis of the bid construction phase with different announcement options. Heuristic solution techniques and an IP formulation help understand the dynamics of the bid construction problem. It is shown that the addition of substitution and partial fulfillment options is essential to diversify and increase the usable capacity of the supplier base. Additionally, the partial fulfillment option enables better usage of supplier inventories in an environment with scarce supplies. © 2012 Elsevier Ltd.
  • Article
    Citation - WoS: 11
    Citation - Scopus: 10
    Ranking Using Promethee When Weights and Thresholds Are Imprecise: a Data Envelopment Analysis Approach
    (Taylor & Francis Ltd, 2022) Eryilmaz, Utkan; Karasakal, Orhan; Karasakal, Esra
    Multicriteria decision making (MCDM) provides tools for the decision makers (DM) to solve complex problems with multiple conflicting criteria. Scalarization of criteria values requires using weights for criteria. Determining weights creates controversy as they are influential on the final ranking and challenges the DM as they are hard to elicit. PROMETHEE method is widely used in MCDM for ranking the alternatives and appropriate in situations when there is limited information on the preference structure of the DM. The DM should provide exact values for parameters such as criteria weights and thresholds of preference functions. Data Envelopment Analysis (DEA) is used for measuring the relative efficiency of alternatives in a non-parametric way without requiring any weight input. In this study, we propose two novel PROMETHEE based ranking approaches that address the determination of weight and threshold values by using an approach inspired by DEA. The first approach can deal with imprecise specification of criteria weights, and the second approach can utilize both imprecise weights and thresholds. The proposed approaches provide the DM substantial flexibility on the required level of information on those parameters. An illustrative example and a real-life case study are presented to show the utility of the proposed approaches.
  • Article
    Citation - WoS: 8
    Citation - Scopus: 9
    Intermodal Humanitarian Logistics Using Unit Load Devices
    (Springer Heidelberg, 2022) Kavlak, Hasan; Ertem, Mustafa Alp; Satir, Benhur
    Intermodal freight transportation facilitates today's global trade. The benefits of intermodal freight transportation have been studied and are more observable in commercial logistics; however, the potential benefits of humanitarian logistics have not been thoroughly investigated. This research aims to present a resilient transportation framework by modeling intermodal transportation utilizing interoperable loading devices during disaster responses. We developed an integer programming model based on a time-space network by considering route and vehicle availabilities that are allowed to change with time. We consider vehicles with varying capacities in three transportation modes (i.e., ground, maritime, and air). The contribution of this study is threefold: (1) Two compatible unit load devices are proposed for humanitarian logistics; (2) a mathematical model that includes integer variable representation for vehicle fleets in different transportation modes is developed; and (3) intermodal transportation is compared with single-mode transportation using a real-life dataset. Our main results are as follows: In terms of cost, intermodal transportation is effective when demand occurs in consecutive periods and response time is short. Inventory is held more in intermodal transportation when it is cost-effective to use transportation modes with large capacities. Thus, the benefits of the responsiveness of intermodal transportation outweigh the costs of mode interchange and inventory holding for sudden-onset disasters where quick responses are needed within a short time.
  • Article
    Citation - WoS: 17
    Citation - Scopus: 19
    Determination of Equivalent Warehouses in Humanitarian Logistics by Reallocation of Multiple Item Type Inventories
    (Elsevier, 2021) Ertem, Mustafa Alp; Demirbas, Sefika
    Prepositioning freight containers for storage of relief supplies can be considered an alternative to warehousing with shelves. Recently, 25 container warehouses are located in different cities in Turkey to deliver relief supplies to beneficiaries quickly. We take this existing situation as given and investigate if this investment could be utilised better. The available inventory (i.e., tents, beds, blankets) in these container warehouses is currently not used efficiently. Some warehouses store one type of item and none from other types. Therefore, several warehouses must be activated during a response operation to fully satisfy the beneficiaries' needs for each relief item type. We aim to investigate the benefits of operating equivalent (i.e., a proper inventory level from each relief item type) warehouses while reallocating a total available inventory for better coordination. A locationreallocation type of mathematical model is tested with real-life data from past earthquakes. Three to eight container warehouses are recommended to be converted to an equivalent type. The results indicate potential savings for the proposed model, and this potential is more visible in large-scale demand instances than in small ones.
  • Article
    Citation - WoS: 23
    Citation - Scopus: 24
    Bi-Objective Dynamic Weapon-Target Assignment Problem With Stability Measure
    (Springer, 2022) Karasakal, Esra; Karasakal, Orhan; Silav, Ahmet
    In this paper, we develop a new bi-objective model for dynamic weapon-target assignment problem. We consider that the initial weapon assignment plan of defense is disrupted during engagement because of a destroyed air target, breakdown of a weapon system or a new incoming air target. The objective functions are defined as the maximization of probability of no-leaker and the maximization of stability in engagement order of weapon systems. Stability is defined as assigning same air target in sequence in engagement order of a weapon system so that reacquisition and re-tracking of air target are not required by sensors. We propose a new solution procedure to generate updated assignment plans by maximizing efficiency of defense while maximizing stability through swapping weapon engagement orders. The proposed solution procedure generates non-dominated solutions from which defense can quickly choose the most-favored course of action. We solve a set of representative problems with different sizes and present computational results to evaluate effectiveness of the proposed approach.
  • Article
    Citation - WoS: 24
    Citation - Scopus: 27
    Bi-Objective Adaptive Large Neighborhood Search Algorithm for the Healthcare Waste Periodic Location Inventory Routing Problem
    (Springer Heidelberg, 2022) Aydemir-Karadag, Ayyuce
    There has been an unexpected increase in the amount of healthcare waste during the COVID-19 pandemic. Managing healthcare waste is vital, as improper practices in the waste system can lead to the further spread of the virus. To develop effective and sustainable waste management systems, decisions in all processes from the source of the waste to its disposal should be evaluated together. Strategic decisions involve locating waste processing centers, while operational decisions deal with waste collection. Although the periodic collection of waste is used in practice, it has not been studied in the relevant literature. This paper integrates the periodic inventory routing problem with location decisions for designing healthcare waste management systems and presents a bi-objective mixed-integer nonlinear programming model that minimizes operating costs and risk simultaneously. Due to the complexity of the problem, a two-step approach is proposed. The first stage provides a mixed-integer linear model that generates visiting schedules to source nodes. The second stage offers a Bi-Objective Adaptive Large Neighborhood Search Algorithm (BOALNS) that processes the remaining decisions considered in the problem. The performance of the algorithm is tested on several hypothetical problem instances. Computational analyses are conducted by comparing BOALNS with its other two versions, Adaptive Large Neighborhood Search Algorithm and Bi-Objective Large Neighborhood Search Algorithm (BOLNS). The computational experiments demonstrate that our proposed algorithm is superior to these algorithms in several performance evaluation metrics. Also, it is observed that the adaptive search engine increases the capability of BOALNS to achieve high-quality Pareto-optimal solutions.
  • Article
    Citation - WoS: 8
    Citation - Scopus: 12
    A Multi-Objective Approach for Dynamic Missile Allocation Using Artificial Neural Networks for Time Sensitive Decisions
    (Springer, 2021) Karasakal, Esra; Silav, Ahmet; Karasakal, Orhan
    In this study, we develop a new solution approach for the dynamic missile allocation problem of a naval task group (TG). The approach considers the rescheduling of the surface-to-air missiles (SAMs), where a set of them have already been scheduled to a set of attacking anti-ship missiles (ASMs). The initial schedule is mostly inexecutable due to disruptions such as neutralization of a target ASM, detecting a new ASM, and breakdown of a SAM system. To handle the dynamic disruptions while keeping efficiency high, we use a bi-objective model that considers the efficiency of SAM systems and the stability of the schedule simultaneously. The rescheduling decision is time-sensitive, and the amount of information to be processed is enormous. Thus, we propose a novel approach that supplements the decision-maker (DM) in choosing a Pareto optimal solution considering two conflicting objectives. The proposed approach uses an artificial neural network (ANN) that includes an adaptive learning algorithm to structure the DM's prior articulated preferences. ANN acts like a DM during the engagement process and chooses one of the non-dominated solutions in each rescheduling time point. We assume that the DM's utility function is consistent with a non-decreasing quasi-concave function, and the cone domination principle is incorporated into the solution procedure. An extensive computational study is provided to present the effectiveness of the proposed approach.