Journal articles: 'Multiproject'

1

Sherstyuk, Katerina. "Multiproject team assignments." Review of Economic Design 4, no. 3 (September 1, 1999): 231–54. http://dx.doi.org/10.1007/s100580050036.

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Kannimuthu, Marimuthu, Palaneeswaran Ekambaram, Benny Raphael, and Ananthanarayanan Kuppuswamy. "Resource Unconstrained and Constrained Project Scheduling Problems and Practices in a Multiproject Environment." Advances in Civil Engineering 2018 (July 15, 2018): 1–13. http://dx.doi.org/10.1155/2018/9579273.

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Construction companies execute many projects simultaneously. In such situations, the performance of one project may influence the others positively or negatively. Construction professionals face difficulties in managing multiple projects in limited resource situations. The purpose of this study is to identify the problems in multiproject scheduling from the practitioner’s perspective and to discover current practices under resource unconstrained and constrained settings. The specific objectives are (1) determining the most challenging issues being faced in handling multiproject environment, (2) enumerating the practices adopted in the industry, and finally (3) identifying the practitioners' perceptions on the multiproject scheduling aspects such as network modeling approaches; activity execution modes; concept of sharing, dedicating, and substituting resources; centralized and decentralized decision-making models; solution approaches; and tools and techniques. An online questionnaire survey was conducted to address the objectives above. The top challenging issues in managing multiproject environment are identified. Factor analysis identified the factors by grouping the variables (a) decision-related, (b) project environment-related, (c) project management-related, and (d) organization-related factors. Resource-unconstrained situation mainly faces the issue of underutilization and wastage of resources leading to lower profit realization. The following findings were identified to overcome the unconstrained resource situation such as identifying the work front, adopting pull planning approach, creating a common resource pool, and allotting it on a rental basis. On the contrary, resource-constrained situation faces the issues of prioritization of resources, coordination, communication, collaboration, quality issues, and rework. The findings suggest the strategies such as top-up via subcontracting, proactive pull planning, introducing buffers, training the culture of the organization towards better communication, coordination, and collaboration, to improve the reliability of achieving baseline project performances. Various multiproject aspects suggested for effective management. The identified problems, practices, and various multiproject aspects are expected to contribute better management of multiproject resource unconstrained and constrained project scheduling.

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Ordoñez, Robert Eduardo Cooper, Mario Vanhoucke, José Coelho, Rosley Anholon, and Olívio Novaski. "A Study of the Critical Chain Project Management Method Applied to a Multiproject System." Project Management Journal 50, no. 3 (March 14, 2019): 322–34. http://dx.doi.org/10.1177/8756972819832203.

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In 1997, Eliyahu Goldratt proposed a method called critical chain project management (CCPM) to minimize the inefficiencies identified in traditional project management. The project management community accepted the proposed method as a viable alternative. However, to allow its implementation with a multiproject system, more research was necessary. Seeking to identify the key factors that influence the performance of the multiproject system applying the CCPM method, we performed a case study. Logistic regression analysis showed that applying the CCPM method in a multiproject system allows for better time estimation of activities and facilitates the allocation of critical resources.

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Van Wegberg, Marc, Arjen Van Witteloostuijn, and Michiel Roscam Abbing. "Multimarket and multiproject collusion." De Economist 142, no. 3 (August 1994): 253–85. http://dx.doi.org/10.1007/bf01431973.

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5

Scheinberg, Mark, and Alan Stretton. "Multiproject planning: tuning portfolio indices." International Journal of Project Management 12, no. 2 (May 1994): 107–14. http://dx.doi.org/10.1016/0263-7863(94)90017-5.

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Spaulding, Aaron, Larry Gamm, Jungyeon Kim, and Terri Menser. "Multiproject Interdependencies in Health Systems Management." Health Care Management Review 39, no. 1 (2014): 31–40. http://dx.doi.org/10.1097/hmr.0b013e31828265f2.

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7

Dean, B. V., D. R. Denzler, and J. J. Watkins. "Multiproject staff scheduling with variable resource constraints." IEEE Transactions on Engineering Management 39, no. 1 (1992): 59–72. http://dx.doi.org/10.1109/17.119663.

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8

Zapalac, Russell, Karen Kuemmler, and Tim Malagon. "Establishing Management Information Systems for Multiproject Programs." Journal of Management in Engineering 10, no. 1 (January 1994): 37–42. http://dx.doi.org/10.1061/(asce)9742-597x(1994)10:1(37).

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9

Paech, B., J. Dorr, and M. Koehler. "Improving requirements engineering communication in multiproject environments." IEEE Software 22, no. 1 (January 2005): 40–47. http://dx.doi.org/10.1109/ms.2005.10.

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Abdel-Hamid, Tarek K. "A multiproject perspective of single-project dynamics." Journal of Systems and Software 22, no. 3 (September 1993): 151–65. http://dx.doi.org/10.1016/0164-1212(93)90107-9.

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11

Patti, Robert. "Lessons Learned from 3D-IC MPW Runs." Additional Conferences (Device Packaging, HiTEC, HiTEN, and CICMT) 2011, DPC (January 1, 2011): 000511–38. http://dx.doi.org/10.4071/2011dpc-ta14.

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Tezzaron has worked for several years in the area of 3D integrated circuit development. During 2010, 3 different multiproject wafer runs targeting 2 to 5 layer 3DICs for several different customers were started. Tezzaron's perspective on the results of those runs, issues, and futures will be discussed.

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Павловська, Людмила Анатоліївна, and Юлія Євгеніївна Прихно. "An experimental research of shipping companies’ multiproject forming." Technology audit and production reserves 2, no. 2(28) (March 29, 2016): 30. http://dx.doi.org/10.15587/2312-8372.2016.66497.

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13

Sathaye, Jayant, Scott Murtishaw, Lynn Price, Maurice Lefranc, Joyashree Roy, Harald Winkler, and Randall Spalding-Fecher. "Multiproject baselines for evaluation of electric power projects." Energy Policy 32, no. 11 (July 2004): 1303–17. http://dx.doi.org/10.1016/s0301-4215(03)00098-3.

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14

Kumara, S. R. T., Y. H. Lee, and K. Chatterjee. "Distributed Multiproject Resource Control: A Market-Based Approach." CIRP Annals 51, no. 1 (2002): 367–70. http://dx.doi.org/10.1016/s0007-8506(07)61538-8.

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15

Kahng, Andrew B., Ion I. Mandoiu, Xu Xu, and Alexander Z. Zelikovsky. "Enhanced Design Flow and Optimizations for Multiproject Wafers." IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems 26, no. 2 (February 2007): 301–11. http://dx.doi.org/10.1109/tcad.2006.883922.

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16

Banaszak, Zbigniew, Grzegorz Bocewicz, and Irena Bach. "CP-driven Production Process Planning in Multiproject Environment." Decision Making in Manufacturing and Services 2, no. 2 (December 18, 2008): 5–32. http://dx.doi.org/10.7494/dmms.2008.2.2.5.

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The way enterprise capabilities are used decides about its competitiveness among other ones. In that context modeling aimed at production tasks allocation planning plays a crucial role especially at concurrently executed production orders. The introduced reference model employing constraint programming (CP) paradigm describes both an enterprise and a set of project-like production orders. Moreover, encompassing consumer orders requirements and available production capabilities, the model provides the formal framework allowing one to develop a class of decision support systems aimed at interactive production process planning subject to multiproject environment constraints. In that context our contribution is a knowledge-based and CP-driven approach to resource allocation assuming precise character of decision variables. The conditions sufficient for deadlock avoidance are the main goal. The conditions delivered provide formal framework for developing a task oriented Decision Support Tool for Project Portfolio Prototyping (DST4P, Banaszak 2006). The tool provides a prompt and interactive service to a set of routine queries formulated either in straight or reverse way.

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17

Lin, Rung-Bin, Meng-Chiou Wu, and Shih-Cheng Tsai. "Reticle Design for Minimizing Multiproject Wafer Production Cost." IEEE Transactions on Automation Science and Engineering 4, no. 4 (October 2007): 589–95. http://dx.doi.org/10.1109/tase.2007.904239.

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18

East, E. William, and Liang Y. Liu. "Multiproject Planning and Resource Controls for Facility Management." Journal of Construction Engineering and Management 132, no. 12 (December 2006): 1294–305. http://dx.doi.org/10.1061/(asce)0733-9364(2006)132:12(1294).

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19

Angling, Michael. "Resource planning and control in a multiproject environment." International Journal of Project Management 6, no. 4 (November 1988): 197–201. http://dx.doi.org/10.1016/0263-7863(88)90002-6.

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20

Dobrynin, Alexey Sergeyevich, Stanislav Matveevich Kulakov, and Alexander Sergeyevich Koynov. "BUILDING UP SCHEDULES IN MULTIPROJECT DESIGN MANAGEMENT SYSTEMS." Vestnik of Astrakhan State Technical University. Series: Management, computer science and informatics 2021, no. 3 (July 30, 2021): 105–14. http://dx.doi.org/10.24143/2072-9502-2021-3-105-114.

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The article focuses on the problem of algorithmizing the process of building schedules in various spheres of human activity by using the modern mathematical apparatus, as well as achievements in the field of systems analysis, game theory, and graph theory. Nowadays, there have been analyzed and determined the boundaries of the effective application of many well-known heuristic and metaheuristic algorithms, which have shown good results in practice. However, despite the achievements in the discrete optimization, scheduling and network planning, the new problems of drawing up so-called coordinated schedules in the field of multi-project planning, which take into account the preferences (requests, wishes) of specific schedule executors, are still of practical interest. There have been considered the approaches and main stages of solving the problems of constructing coordinated schedules in multi-project planning, which is relevant for the development of new generation software and tools

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21

Gang, Jun, Jiuping Xu, and Yinfeng Xu. "Multiproject Resources Allocation Model under Fuzzy Random Environment and Its Application to Industrial Equipment Installation Engineering." Journal of Applied Mathematics 2013 (2013): 1–19. http://dx.doi.org/10.1155/2013/818731.

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This paper focuses on a multiproject resource allocation problem in a bilevel organization. To solve this problem, a bilevel multiproject resource allocation model under a fuzzy random environment is proposed. Two levels of decision makers are considered in the model. On the upper level, the company manager aims to allocate the company's resources to multiple projects to achieve the lowest cost, which include resource costs and a tardiness penalty. On the lower level, each project manager attempts to schedule their resource-constrained project, with minimization of project duration as the main objective. In contrast to prior studies, uncertainty in resource allocation has been explicitly considered. Specifically, our research uses fuzzy random variables to model uncertain activity durations and resource costs. To search for the optimal solution of the bilevel model, a hybrid algorithm made up of an adaptive particle swarm optimization, an adaptive hybrid genetic algorithm, and a fuzzy random simulation algorithm is also proposed. Finally, the efficiency of the proposed model and algorithm is evaluated through a practical case from an industrial equipment installation company. The results show that the proposed model is efficient in dealing with practical resource allocation problems in a bilevel organization.

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22

Benediktsson, O., D. Dalcher, and H. Thorbergsson. "Comparison of software development life cycles: a multiproject experiment." IEE Proceedings - Software 153, no. 3 (2006): 87. http://dx.doi.org/10.1049/ip-sen:20050061.

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23

Liu, Shu-Shun, and Chang-Jung Wang. "Profit Optimization for Multiproject Scheduling Problems Considering Cash Flow." Journal of Construction Engineering and Management 136, no. 12 (December 2010): 1268–78. http://dx.doi.org/10.1061/(asce)co.1943-7862.0000235.

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24

Korhonen, Tuomas, Teemu Laine, Jouni Lyly-Yrjänäinen, and Petri Suomala. "Innovation for Multiproject Management: The Case of Component Commonality." Project Management Journal 47, no. 2 (April 2016): 130–43. http://dx.doi.org/10.1002/pmj.21586.

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25

Van Cayseele, Patrick. "Spillovers and the cost of multiproject R&D." Managerial and Decision Economics 7, no. 2 (June 1986): 133–39. http://dx.doi.org/10.1002/mde.4090070210.

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26

Wang, Weixin, Jiafu Su, Jin Xu, and Xianlong Ge. "Reactive Strategies in the Multiproject Scheduling with Multifactor Disruptions." Mathematical Problems in Engineering 2020 (May 30, 2020): 1–11. http://dx.doi.org/10.1155/2020/3154047.

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Multiproject scheduling aims at the generation of the baseline schedules, which has been studied for several years with the goal of minimizing the total cost of the project. In this paper, we analyzed the impact of network structure disruption, activity disruption, and resource disruption on scheduling scheme, respectively; this problem is related to the disruptions in scheduling process, which leads to a deviation between actual scheduling and baseline scheduling. The mode of the related activities is changed and the start time is reset. Because it is a NP-hard problem and involves a large number of activities, the dual population genetic algorithm is designed to solve this problem. From the results of case analysis, we find that single disruption on scheduling was local, when there was no resource conflict. While multifactor disruptions have greater effect on duration and total cost, multifactor disruptions would affect each other, so it was more complicated.

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27

Roetheli, Rudolph, and Peter Pesenti. "Portfolio method — a control tool in the multiproject organization." International Journal of Project Management 4, no. 2 (May 1986): 87–90. http://dx.doi.org/10.1016/0263-7863(86)90034-7.

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28

Snyder, Christopher M., and Nicholas S. Vonortas. "Multiproject contact in research joint ventures: evidence and theory." Journal of Economic Behavior & Organization 58, no. 4 (December 2005): 459–86. http://dx.doi.org/10.1016/j.jebo.2004.03.007.

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29

Zapata, Juan Camilo, Bri Mathias Hodge, and Gintaras V. Reklaitis. "The multimode resource constrained multiproject scheduling problem: Alternative formulations." AIChE Journal 54, no. 8 (August 2008): 2101–19. http://dx.doi.org/10.1002/aic.11522.

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30

Gati, Ana Maria, and Paulo Tromboni. "Manufacturing role in simple product development at a multiproject environment." Product Management & Development 10, no. 1 (2012): 61–70. http://dx.doi.org/10.4322/pmd.2012.015.

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31

Swanson, J. G., and J. P. Tilston. "A Solution to the Pin-Out Problem in Multiproject Chips." International Journal of Electrical Engineering & Education 26, no. 1-2 (January 1989): 121–26. http://dx.doi.org/10.1177/002072098902600118.

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Combining several relatively small student designs on one chip awkwardly reduces the number of external connections per design. A multiplexing scheme is described which allows four students to each use 31 pins on a 40-pin package. The implentation of this scheme in a 2 μm full-custom CMOS technology is reported.

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32

Kurtulus, Ibrahim. "Multiproject scheduling: Analysis of scheduling strategies under unequal delay penalties." Journal of Operations Management 5, no. 3 (May 1985): 291–307. http://dx.doi.org/10.1016/0272-6963(85)90015-4.

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33

Lova, Antonio, Concepción Maroto, and Pilar Tormos. "A multicriteria heuristic method to improve resource allocation in multiproject scheduling." European Journal of Operational Research 127, no. 2 (December 2000): 408–24. http://dx.doi.org/10.1016/s0377-2217(99)00490-7.

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34

Sonmez, Rifat, and Furkan Uysal. "Backward-Forward Hybrid Genetic Algorithm for Resource-Constrained Multiproject Scheduling Problem." Journal of Computing in Civil Engineering 29, no. 5 (September 2015): 04014072. http://dx.doi.org/10.1061/(asce)cp.1943-5487.0000382.

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35

Maniak, Rémi, and Christophe Midler. "Multiproject lineage management: Bridging project management and design-based innovation strategy." International Journal of Project Management 32, no. 7 (October 2014): 1146–56. http://dx.doi.org/10.1016/j.ijproman.2014.03.006.

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36

Koch-Ørvad, Nina, Christian Thuesen, Christian Koch, and Thomas Berker. "Transforming Ecosystems: Facilitating Sustainable Innovations Through the Lineage of Exploratory Projects." Project Management Journal 50, no. 5 (September 3, 2019): 602–16. http://dx.doi.org/10.1177/8756972819870623.

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Radical innovations are essential for the sustainable transition of society; however, such innovations are struggling to establish a solid position in the ecosystem. Through a case study, the influence of the ecosystem on a radical, sustainable innovation is investigated. The study shows that the ecosystem causes bottleneck challenges for the innovation and that a lineage of exploratory projects is essential to transforming the ecosystem and thereby supporting the breakthrough of the innovation. A model for lineage ecosystem management is proposed, extending and contributing to the multiproject lineage management approach, with a particular focus on radical, sustainable innovations.

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37

Korb, Samuel, and Rafael Sacks. "Agent-Based Simulation of General Contractor–Subcontractor Interactions in a Multiproject Environment." Journal of Construction Engineering and Management 147, no. 1 (January 2021): 04020151. http://dx.doi.org/10.1061/(asce)co.1943-7862.0001944.

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38

García-Gómez, Juan M., Jan Luts, Margarida Julià-Sapé, Patrick Krooshof, Salvador Tortajada, Javier Vicente Robledo, Willem Melssen, et al. "Multiproject–multicenter evaluation of automatic brain tumor classification by magnetic resonance spectroscopy." Magnetic Resonance Materials in Physics, Biology and Medicine 22, no. 1 (November 7, 2008): 5–18. http://dx.doi.org/10.1007/s10334-008-0146-y.

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39

Wirth, Itzhak, and Aharon Hibshoosh. "Decision support system for multiproject scheduling of resources in blood collection programmes." International Journal of Project Management 6, no. 4 (November 1988): 202–10. http://dx.doi.org/10.1016/0263-7863(88)90003-8.

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40

A Kurstedt, H., E. J Gardner, and T. B Hindman. "Design and use of a flat structure in a multiproject research organization." International Journal of Project Management 9, no. 4 (November 1991): 210–15. http://dx.doi.org/10.1016/0263-7863(91)90028-t.

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41

Toffolo, Túlio A. M., Haroldo G. Santos, Marco A. M. Carvalho, and Janniele A. Soares. "An integer programming approach to the multimode resource-constrained multiproject scheduling problem." Journal of Scheduling 19, no. 3 (April 16, 2015): 295–307. http://dx.doi.org/10.1007/s10951-015-0422-4.

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42

Gibson, Pamela Reed, Arnold S. Kahn, and Virginia Andreoli Mathie. "Undergraduate Research Groups: Two Models." Teaching of Psychology 23, no. 1 (February 1996): 36–38. http://dx.doi.org/10.1207/s15328023top2301_7.

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Research suggests that participation in out-of-class research projects is a valuable experience for undergraduate psychology students. At many academic institutions, however, limited resources and large numbers of majors preclude requiring all students to participate in one-on-one research opportunities with faculty. In an effort to offer research experience to as many students as possible, some departments have instituted research teams. We describe two research team models that have worked well at a mid-size university. Model 1 is a single-faculty, single-project team, and Model 2 is a large multifaculty, multiproject team. Faculty and students find that this team approach is a valuable way to meet their research needs.

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43

Midler, Christophe. "Implementing a Low-End Disruption Strategy through Multiproject Lineage Management: The Logan Case." Project Management Journal 44, no. 5 (October 2013): 24–35. http://dx.doi.org/10.1002/pmj.21367.

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44

Ward, Martin F., Angie Titchen, Clare Morrell, Brendan McCormack, and Alison Kitson. "Using a supervisory framework to support and evaluate a multiproject practice development programme." Journal of Clinical Nursing 7, no. 1 (January 1998): 29–36. http://dx.doi.org/10.1046/j.1365-2702.1998.00135.x.

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45

Ash, Robert, and Dwight E. Smith-Daniels. "The Effects of Learning, Forgetting, and Relearning on Decision Rule Performance in Multiproject Scheduling." Decision Sciences 30, no. 1 (January 1999): 47–82. http://dx.doi.org/10.1111/j.1540-5915.1999.tb01601.x.

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46

He, Yukang, Jingwen Zhang, and Zhengwen He. "Metaheuristic Algorithms for Multimode Multiproject Scheduling With the Objective of Positive Cash Flow Balance." IEEE Access 7 (2019): 157427–36. http://dx.doi.org/10.1109/access.2019.2944746.

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47

Platje, A., and H. Seidel. "Breakthrough in multiproject management: how to escape the vicious circle of planning and control." International Journal of Project Management 11, no. 4 (November 1993): 209–13. http://dx.doi.org/10.1016/0263-7863(93)90037-n.

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48

Xu, Bin, Weiguo Fang, Ruifeng Shi, Jing Yu, and Lu Liu. "Three-objective fuzzy chance-constrained programming model for multiproject and multi-item investment combination." Information Sciences 179, no. 5 (February 2009): 623–41. http://dx.doi.org/10.1016/j.ins.2008.10.031.

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49

Shou, Yongyi, Wenwen Xiang, Ying Li, and Weijian Yao. "A Multiagent Evolutionary Algorithm for the Resource-Constrained Project Portfolio Selection and Scheduling Problem." Mathematical Problems in Engineering 2014 (2014): 1–9. http://dx.doi.org/10.1155/2014/302684.

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A multiagent evolutionary algorithm is proposed to solve the resource-constrained project portfolio selection and scheduling problem. The proposed algorithm has a dual level structure. In the upper level a set of agents make decisions to select appropriate project portfolios. Each agent selects its project portfolio independently. The neighborhood competition operator and self-learning operator are designed to improve the agent’s energy, that is, the portfolio profit. In the lower level the selected projects are scheduled simultaneously and completion times are computed to estimate the expected portfolio profit. A priority rule-based heuristic is used by each agent to solve the multiproject scheduling problem. A set of instances were generated systematically from the widely used Patterson set. Computational experiments confirmed that the proposed evolutionary algorithm is effective for the resource-constrained project portfolio selection and scheduling problem.

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50

Hematian, Milad, Mir Mehdi Seyyed Esfahani, Iraj Mahdavi, Nezam Mahdavi‐Amiri, and Javad Rezaeian. "A multiobjective integrated multiproject scheduling and multiskilled workforce assignment model considering learning effect under uncertainty." Computational Intelligence 36, no. 1 (December 2019): 276–96. http://dx.doi.org/10.1111/coin.12260.

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Journal articles on the topic 'Multiproject'

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