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Strategic planning of new product introductions: Integrated planning of products and modules in the automotive industry

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OMEGA-INTERNATIONAL JOURNAL OF MANAGEMENT SCIENCE 2021年 105卷 102515-102515页

作者： Bersch, Christopher, V Akkerman, Renzo Kolisch, Rainer Tech Univ Munich TUM Sch Management Arcisstr 21 D-80333 Munich Germany Wageningen Univ Operat Res & Logist Grp Hollandseweg 1 NL-6706 KN Wageningen Netherlands

Timing the introduction of new products to the market is an important strategic decision in the automotive industry. For several reasons, it is also a complex decision problem. First, the use of platforms creates many interactions between different vehicles via shared modules (e.g. engines). Second, new and existing products rely on various shared resources (e.g. development resources or production capacities). Furthermore, different conflicting objectives must be considered. In this paper, we develop a mathematical linear programming model describing the decision problem based on the resource-constrained project scheduling problem. It simultaneously decides on the start of production date for vehicle models, variants, and engines as well as on the assignment of engines to the given variants. Integrating a multicriteria approach, the model helps to analyze trade-offs between important managerial objectives related to resource utilization and fleet emission metrics. Using realistic data from a major European automotive company, we demonstrate that our model enables the efficient evaluation of various courses of action. Such capabilities are especially relevant in times of rapid technological change, such as the current transition towards electrified vehicle portfolios. (C) 2021 The Author(s). Published by Elsevier Ltd.

关键词： mixed integer programming Modularization Strategic planning and management Resource utilization

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A mathematical modelling approach for planning health resources after earthquake: Kirikkale city example

JOURNAL OF THE FACULTY OF ENGINEERING AND ARCHITECTURE OF GA...

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JOURNAL OF THE FACULTY OF ENGINEERING AND ARCHITECTURE OF GAZI UNIVERSITY 2023年第2期38卷 1203-1216页

作者： Ciftci, Sema Sakalli, Umit Sami Ostim Tech Univ Fac Engn Dept Ind Engn TR-06374 Ankara Turkiye Kirikkale Univ Fac Engn Dept Ind Engn TR-71450 Yahsihan Kirikkale Turkiye

Earthquakes are the most common type of disaster, which causes life and property loss. After the earthquake, chaotic conditions make the intervention and recovery process difficult. In the management of this process, the resources available (health, shelter, AFAD teams, etc.) it is necessary to successfully allocate it to the debris areas. In the early hours after the earthquakes, the injured are more likely to survive in relation to the severity of injury (heavy and detertable wounded) and in the correct proportion of the time elapsed;as time progresses, this is less likely. Therefore, the first intervention of the injured from the wreckage must be carried out and those in need must be rushed to the hospital. Therefore, health resources planning is crucial to reducing the devastating effects of the earthquake. In this study, a mathematical model of 0-1 mixed numbers was developed, aimed at minimizing the number of injured people who lost their lives after the earthquake. In the model, it is requested to assign health units (doctors, nurses, equipment) to perform crime scene triage to the debris areas, assign ambulances to the hospital for the transfer of injured people who have been triyed at the crime scene, and to decide which hospitals the ambulances should be directed to. The modeling of the model as a markov chain of health changes in the multi -period and injured people is a contributor to literature. The developed model was tested using the GAMS CPLEX solver with possible earthquake scenario data for the Kirikkale province. The test results show that the model developed can be used as an effective planning tool for healthcare allocation.

关键词： Earthquake resources allocation planning mathematical model mixed integer programming

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Access and Resource Management for Clinical Care and Clinical Research in Multi-class Stochastic Queueing Networks.

Access and Resource Management for Clinical Care and Clinica...

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作者： Deglise-Favre-Hawkinson, Jivan University of Michigan

In healthcare delivery systems, proper coordination between patient visits and the health care resources they rely upon is an area in which important new planning capabilities are very valuable to provide greater value to all stakeholders. Managing supply and demand, while providing an appropriate service level for various types of care and patients of differing levels of urgency is a difficult task to achieve. This task becomes even more complex when planning for (i) stochastic demand, (ii) multi-class customers (i.e., patients with different urgency levels), and (iii) multiple services/visit types (which includes multi-visit itineraries of clinical care and/or clinical research visits that are delivered according to research protocols). These complications in the demand stream require service waiting times and itineraries of visits that may span multiple days/weeks and may utilize many different resources in the organization (each resource with at least one specific service being provided). The key objective of this dissertation is to develop planning models for the optimization of capacity allocation while considering the coordination between resources and patient demand in these multi-class stochastic queueing networks in order to meet the service/access levels required for each patient class. This control can be managed by allocating resources to specific patient types/visits over a planning horizon. In this dissertation, we control key performance metrics that relate to patient access management and resource capacity planning in various healthcare settings with chapters devoted to outpatient services, and clinical research units. The methods developed forecast and optimize (1) the access to care (in a medical specialty) for each patient class, (2) the Time to First Available Visit for clinical research participants enrolling in clinical trials, and (3) the access to downstream resources in an itinerary of care, which we call the itinerary flow time. We also

关键词： Capacity Planning Access Management Patient Scheduling mixed integer programming Resource and Demand Coordination Thesis

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A Distributed Electric Vehicle Charging Scheduling Platform Considering Aggregators Coordination

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IEEE ACCESS 2021年 9卷 151294-151305页

作者： Afshar, Shahab Disfani, Vahid Siano, Pierluigi Univ Tennessee ConnectSmart Res Lab Chattanooga TN 37403 USA Univ Salerno Dept Management & Innovat Syst I-84084 Salerno Italy

In this paper, a two-layer distributed optimization platform employing the alternating direction method of multipliers (ADMM) method is developed as an exchange problem to solve the electric vehicle charging management problem (EVCMP). The proposed model establishes a coordination layer between the EV aggregators, which increases the optimization's overall efficiency while preserving aggregators' independence. Numerical tests validate that the proposed coordinated distributed platform (CDP) enhances the load profile's smoothness compared to the locally coordinated and uncoordinated charging platforms. Moreover, CDP also decreases the total EV charging costs by 35%, compared to the uncoordinated charging approach.

关键词： Batteries Optimization Costs Degradation Electric vehicle charging Load modeling Collaboration Alternative direction method of multipliers battery degradation distributed optimization electric vehicle aggregation mixed integer programming

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Assessment of the Modeling of Demand Response as a Dispatchable Resource in Day-Ahead Hydrothermal Unit Commitment Problems: The Brazilian Case

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ENERGIES 2022年第11期15卷 3928页

作者： Santos, Rosane Diniz, Andre Luiz Borba, Bruno UFF Fed Fluminense Univ Elect Engn Dept BR-24210240 Niteroi RJ Brazil CEPEL Brazilian Elect Energy Res Ctr BR-21941911 Rio De Janeiro Brazil

Modern power systems have experienced large increases in intermittent and non-dispatchable sources and a progressive reduction in the size of hydro reservoirs for inflow regularization. One method to mitigate the high uncertainty and intermittency of the net load is by Demand Response (DR) mechanisms, to allow a secure and reliable system dispatch. This work applied a mixed integer linear programming formulation to model DR as a dispatchable resource in the day-ahead hydrothermal scheduling problem, taking into account minimum load curtailment constraints, minimum up/down load deduction times, as well as piecewise linear bid curves for load shedding in eligible loads. The methodology was implemented in the official model used in Brazil and tested in large-scale problems to obtain the optimal daily dispatch and hourly pricing. The results show the positive impact of dispatchable DR loads in cost reduction and in mitigating peak values of energy prices, even for predominantly hydro systems, helping to preserve the reservoir levels and increasing the security of the supply in the future.

关键词： day-ahead dispatch demand response hydrothermal scheduling mixed integer programming unit commitment

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The Use of Unmanned Aerial Vehicles for Dynamic Site Layout Planning in Large-Scale Construction Projects

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BUILDINGS 2021年第12期11卷 602-602页

作者： Hammad, Ahmed W. A. da Costa, Bruno B. F. Soares, Carlos A. P. Haddad, Assed N. Univ New South Wales UNSW Built Environm Sydney NSW 2052 Australia Univ Fed Rio de Janeiro Inst Politecn BR-27930560 Macae Brazil Univ Fed Fluminense Dept Engn Civil BR-24210240 Niteroi RJ Brazil Univ Fed Rio de Janeiro Programa Engn Ambiental BR-21941901 Rio De Janeiro Brazil

Construction sites are increasingly complex, and their layout have an impact on productivity, safety, and efficiency of construction operations. Dynamic site layout planning (DSLP) considers the adjustment of construction facilities on-site, on an evolving basis, allowing the relocation of temporary facilities according to the stages of the project. The main objective of this study is to develop a framework for integrating unmanned aerial vehicles (UAVs) and their capacity for effective photogrammetry with site layout planning optimisation and Building Information Modelling (BIM) for automating site layout planning in large construction projects. The mathematical model proposed is based on a mixed integer programming (MIP) model, which was employed to validate the framework on a realistic case study provided by an industry partner. Allocation constraints were formulated to ensure the placement of the facilities in feasible regions. Using information from the UAV, several parameters could be considered, including proximity to access ways, distances between the facilities, and suitability of locations. Based on the proposed framework, a layout was developed for each stage of the project, adapting the location of temporary facilities according to current progress on-site. As a result, the use of space was optimised, and internal transport costs were progressively reduced.

关键词： unmanned aerial vehicle dynamic site layout construction planning optimisation mixed integer programming construction management

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UAV routing for reconnaissance mission: A multi-objective orienteering problem with time-dependent prizes and multiple connections

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COMPUTERS & OPERATIONS RESEARCH 2022年 145卷 1页

作者： Dasdemir, Erdi Batta, Rajan Koksalan, Murat Ozturk, Diclehan Tezcaner Hacettepe Univ Dept Ind Engn TR-06800 Ankara Turkey Univ Buffalo SUNY Dept Ind & Syst Engn Buffalo NY 14260 USA Middle East Tech Univ Dept Ind Engn TR-06800 Ankara Turkey Univ Michigan Ross Sch Business Ann Arbor MI 48109 USA

We address the route planning problem of an unmanned air vehicle (UAV) tasked with collecting information from a radar-monitored environment for a reconnaissance mission. The UAV takes off from a home base, visits a set of targets, and finishes its movement at a final base. Collectable information at a target depends on the time the target is visited by the UAV. There are multiple trajectory alternatives between the target pairs with different travel time and threat attributes. A route plan involves the selection of the targets to visit, the order of visit to the targets, and the trajectories to follow between the targets. Multiple routing objectives, information collection, mission duration and mission safety, are considered to present the trade-offs among the objectives to the route planner. The problem is classified as a multi-objective orienteering problem with time-dependent prizes and multiple connection options. A mixed integer programming model that can be used for small-sized problems is formulated. Larger problems are addressed with a hybrid algorithm involving heuristics and exact approaches. A case study based on a terrain in the State of Colorado is presented. Finally, some practical issues for the UAV route planning problem is discussed.

关键词： Multiple objective programming UAV routing Orienteering Time-dependent prizes mixed integer programming

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The surgical case scheduling problem with fuzzy duration time: An ant system algorithm

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SCIENTIA IRANICA 2019年第3期26卷 1824-1841页

作者： Behmanesh, R. Zandieh, M. Molana, S. M. Hadji Islamic Azad Univ Dept Ind Engn Sci & Res Branch Tehran Iran Shahid Beheshti Univ Fac Management & Accounting Dept Ind Management GC Tehran Iran

In this paper, we address the surgical case scheduling problem in multi-operating theater environment with uncertain service times in order to minimize makespan. In surgical case scheduling, not only the hospital resources are allocated to surgical cases, but also the start time of performing surgeries is determined based on a sequence of cases in a short-term time horizon. We consider fuzzy numbers for duration times of all stages and hereafter, the problem is called fuzzy surgical case scheduling. Since the operational environment in the problem is similar to no-wait multi-resource fuzzy flexible job shop problem, we consider constraints of the latter for formulating and solving the problem. This problem is strongly an NP-hard optimization problem, hence we employ ant system algorithm to tackle it. The proposed approach is illustrated by detailed examples of three test cases and numerical computational experiments. The performance of the proposed algorithm is compared with a schedule constructed by first-come-first-service rule in all test instances. Also, a real case is provided from a hospital in Isfahan to evaluate the proposed algorithm. The computational experiments state that the algorithm outperforms hospital planning as well as fuzzy rule, indicating efficiency and capability of the algorithm for optimizing the makespan. (C) 2019 Sharif University of Technology. All rights reserved.

关键词： Surgical case scheduling Ant system Operating theater Fuzzy duration time Makespan mixed integer programming

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A heuristic scheduling approach for fog-cloud computing environment with stationary IoT devices

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JOURNAL OF NETWORK AND COMPUTER APPLICATIONS 2021年 180卷 102994-102994页

作者： Aburukba, Raafat O. Landolsi, Taha Omer, Dalia Amer Univ Shrjah Dept Comp Sci & Engn Sharjah U Arab Emirates

The emergence of the Internet of Things (IoT) paradigm has led to the rise of a variety of applications with different characteristics and Quality of Service (QoS) requirements. Those applications require computational power and have time sensitive requirements. Cloud computing paradigm provides an illusion to consumers with unlimited computation resource power. However, cloud computing fails to deliver on the time-sensitive requirements of applications. The main challenge in the cloud computing paradigm is the associated delays from the edge IoT device to the cloud data center and from the cloud data center back to the edge device. Fog computing extends limited computational services closer to the edge device to achieve the time sensitive requirement of applications. This work proposes a scheduling solution which adopts the three-tier fog computing architecture in order to satisfy the maximum number of requests given their deadline requirements. In this work, an optimization model using mixed integer programming is introduced to minimize deadline misses. The model is validated with an exact solution technique. The scheduling problem is known to be an NP-hard, and hence, exact optimization solutions are inadequate for a typical size problem in fog computing. Given the complex nature of the problem, a heuristic approach using the genetic algorithm (GA) is presented. The performance of the proposed GA was evaluated and compared against round robin and priority scheduling. The results show that the deadline misses of the proposed approach is 20%?55% better than the other techniques.

关键词： Fog-cloud computing Task scheduling mixed integer programming Number of deadline misses Genetic algorithm

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A MATHEMATICAL MODEL FOR THE CAPACITATED LOCATION-ARC ROUTING PROBLEM WITH DEADLINES AND HETEROGENEOUS FLEET

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TRANSPORT 2019年第6期34卷 692-707页

作者： Mirzaei-Khafri, Soheila Bashiri, Mahdi Soltani, Roya Khalilzadeh, Mohammad Islamic Azad Univ Dept Ind Engn Sci & Res Branch Tehran Iran Coventry Univ Fac Business & Law Sch Strategy & Leadership Coventry W Midlands England Khatam Univ Dept Ind Engn Tehran Iran

This paper considers a Capacitated Location-Arc Routing Problem (CLARP) with Deadlines (CLARPD) and a fleet of capacitated heterogeneous vehicles. The proposed mixed integer programming model determines a subset of potential depots to be opened, the served roads within predefined deadlines, and the vehicles assigned to each open depot. In addition, efficient routing plans are determined to minimize total establishment and traveling costs. Since the CLARP is NP-hard, a Genetic Algorithm (GA) is presented to consider proposed operators, and a constructive heuristic to generate initial solutions. In addition, a Simulated Annealing (SA) algorithm is investigated to compare the performance of the GA. Computational experiments are carried out for several test instances. The computational results show that the proposed GA is promising. Finally, sensitivity analysis confirms that the developed model can meet arc routing timing requirements more precisely compared to the classical Capacitated Arc Routing Problem (CARP).

关键词： capacitated location-arc routing mixed integer programming deadlines genetic algorithm simulated annealing heterogeneous fleet

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