با سلام خدمت کاربران عزیز، به اطلاع می رساند ترجمه مقالاتی که سال انتشار آن ها زیر 2008 می باشد رایگان بوده و میتوانید با وارد شدن در صفحه جزییات مقاله به رایگان ترجمه را دانلود نمایید.
Pharmaceutical R & D pipeline management under trial duration uncertainty
مدیریت خط لوله تحقیق و توسعه دارویی تحت عدم قطعیت آزمایش-2020
We consider a pharmaceutical Research & Development (R & D) pipeline management problem under two significant uncertainties: the outcomes of clinical trials and their durations. We present an Approximate Dynamic Programming (ADP) approach to solve the problem efficiently. Given an initial list of potential drug candidates, ADP derives a policy that suggests the trials to be performed at each decision point and state. For the classical R&D pipeline planning problem with deterministic trial durations, we compare our ADP approach with other methods from the literature, and find that it can find better solutions more quickly in particular for larger problem instances. For the case with stochastic trial durations, we compare the ADP algorithm with a myopic approach and show that the expected net profit obtained by the derived ADP policy is higher (almost 20% for a 10-drug portfolio).
Keywords: Dynamic programming | Pharmaceutical R&D pipeline management | Heuristics | Approximate dynamic programming | Project scheduling
A two-stage multi-operator differential evolution algorithm for solving Resource Constrained Project Scheduling problems
یک الگوریتم تکامل دیفرانسیل چند مرحله ای چند کاره برای حل مشکلات برنامه ریزی پروژه محدود شده از منابع-2020
The Resource Constrained Project Scheduling problem (RCPSP) is a complex and combinatorial optimization problem mostly relates with project management, construction industries, production planning and manufacturing domains. Although several solution methods have been proposed, no single method has been shown to be the best. Further, optimal solution of this type of problem requires different requirements of the exploration and exploitation at different stages of the optimization process. Considering these requirements, in this paper, a two-stage multi-operator differential evolution (DE) algorithm, called TS-MODE, has been developed to solve RCPSP. TS-MODE starts with the exploration stage, and based on the diversity of population and the quality of solutions, this approach dynamically place more importance on the most-suitable DE, and then repeats the same process during the exploitation phase. A complete evaluation of the components and parameters of the algorithms by a Design of Experiments technique is also presented. A number of single-mode RCPSP data sets from the project scheduling library (PSPLIB) have been considered to test the effectiveness and performance of the proposed TS-MODE against selected recent well-known state-of-the-art algorithms. Those results reveal the efficiency and competitiveness of the proposed TS-MODE approach.
Keywords: Evolutionary algorithms | Differential evolution | Adaptive operator selection | Resource constrained project scheduling | problems
Mean-conditional value at risk model for the stochastic project scheduling problem
ارزش میانگین شرطی در مدل ریسک برای مسئله برنامه ریزی تصادفی پروژه-2020
Every project faces different opportunities and risks during its lifecycle. Risks are the factors that can disrupt the successful implementation of projects and cause failure in achieving project goals. Advancing the project while considering its risks is one of the most essential aspects of project management. Planning and scheduling can be applied in a way that reduces the risks in the management of projects. In this paper, a new scenario-based meanconditional value-at-risk (CVaR) model is developed to minimize the risk of the project’s net present value (NPV). Moreover, the trade-off between expected NPV and the risk of NPV is considered in this study. Start time policies are also used to specify the start times of project activities. Two multi-objective optimization algorithms including Non-dominated Sorting Genetic Algorithms (NSGA-II), and Multi-Objective Vibration Damping Optimization (MOVDO) are applied to identify the Pareto optimal solution. The efficiency of the algorithms is assessed based on some performance criteria. The results of the computational experiments show that at identical run time MOVDO functions better in terms of hypervolume indicator, while NSGA- II better results in other performance metrics
Keywords: Stochastic project scheduling | Conditional-value-at risk | Scheduling policy
A survey of hybrid metaheuristics for the resource-constrained project scheduling problem
بررسی استعاره ترکیبی برای مشکل برنامه ریزی پروژه با محدودیت منابع-2020
The Resource-Constrained Project Scheduling Problem (RCPSP) is a general problem in scheduling that has a wide variety of applications in manufacturing, production planning, project management, and var- ious other areas. The RCPSP has been studied since the 1960s and is an NP-hard problem. As being an NP-hard problem, solution methods are primarily heuristics. Over the last two decades, the increasing interest in operations research for metaheuristics has resulted in a general tendency of moving from pure metaheuristic methods for solving the RCPSP to hybrid methods that rely on different metaheuristic strategies. The purpose of this paper is to survey these hybrid approaches. For the primary hybrid meta- heuristics that have been proposed to solve the RCPSP over the last two decades, a description of the basic principles of the hybrid metaheuristics is given, followed by a comparison of the results of the dif- ferent hybrids on the well-known PSPLIB data instances. The distinguishing features of the best hybrids are also discussed.
Keywords: Project scheduling| Resource constraints | RCPSP | Metaheuristics | Hybrids
Project schedule performance under general mode implementation disruptions
عملکرد برنامه پروژه تحت اختلال در اجرای کلی حالت-2020
This paper presents a simulation study for a resource-constrained project scheduling problem with mul- tiple alternatives. We decide on a set of baseline schedules at the project planning phase, resulting in options to switch between execution modes of activities during project execution. We assess the perfor- mance of the set of baseline schedules under general mode implementation disruptions. A simple, yet effective algorithm is presented to construct the set of baseline schedules. Moreover, a general disruption system is proposed to model different disruption types, disruption dependencies and disruption sizes.
Keywords: Project management | Execution alternatives | Matheuristic | Disruption system
Optimizing temporary work and overtime in the Time Cost Quality Trade-offProblem
بهینه سازی کار موقت و اضافه کاری در مسٔله تقابل کیفیت هزینه زمان -2020
In spite of its significant contribution to project success, quality has been scarcely addressed in the lit- erature on deterministic project scheduling problems. Although it is recognized that higher qualities are associated with longer processing times, no relationship between quality and resource consumption has been analytically derived to support this statement. As manufacturing projects can be accelerated us- ing additional manpower such as overtime and temporary workers, we derive an analytical relationship between quality and manpower since overtime and overmanning negate quality. We also take into ac- count productivity losses due to overmanning. Contrary to most previous contributions that focus on the project overall quality as an aggregation of quality levels attained at the individual activities, we impose each activity to reach a minimum quality threshold, which is consistent with project management prac- tices. Consequently, we develop a mixed integer linear programming (MILP) to optimize temporary work and overtime so as to accelerate a project with quality and productivity considerations. The objective is to simultaneously determine for each activity the number of permanent, temporary and overtime work- ers over the processing periods in order to minimize the makespan, the total cost and the overall quality losses subject to individual quality constraints, precedence relationships, nonpreemption and availability of resources. Our approach is successfully applied on numerous instances based on a real project of a high speed locomotive as well as on other projects taken from the literature.
Keywords: Project scheduling | Time Cost Quality Trade-offProblem | Activity quality | Temporary work | Overtime
A classification and review of approaches and methods for modeling uncertainty in projects
طبقه بندی و بررسی رویکردها و روشها برای مدل سازی عدم اطمینان در پروژه ها-2020
In this paper, we created a classification for major sources of uncertainty in projects and categorized the studies in project scheduling literature with respect to the uncertainty source(s) they address. In addition, we investi- gated the approaches and methods to manage uncertainty, and studied the literature regarding these methods. Project management predominantly models the randomness in duration of activities; however, studies modeling the uncertainty due to other sources are scarce. We focused on these sources of uncertainty and highlighted the promising areas of research. The results presented in this paper will help researchers to identify the research gaps in modeling project uncertainty.
Keywords: Project management | Project scheduling | Uncertainty | Stochastic scheduling | Robust scheduling | Reactive scheduling
Work package-based information modeling for resource-constrained scheduling of construction projects
مدل سازی اطلاعات مبتنی بر بسته کار برای برنامه ریزی محدود منابع از پروژه های ساختمانی-2020
As an essential problem in construction management, the resource-constrained project scheduling problem (RCPSP) has been studied for decades; however, an integrated information model that fully supports the RCPSP solving process is still lacking. Though building information modeling (BIM) was proposed to meet the data requirements in the building life cycle, some scheduling and resource information are not considered in information transfers between the information model and the RCPSP mathematical model. This paper presents an integrated approach that enables fluent data flow from the information model to the RCPSP model for construction scheduling. Within this approach, a work package-based information model is proposed to capture all the required data of the RCPSP. Then, a semiautomatic method that integrates multisource data is introduced to form the proposed information model, and an adaptive data transmission method is used to support a designed multimode resource-constrained project scheduling problem (MRCPSP) model. The models and approaches are validated using the data of an actual project, demonstrating the feasibility and efficiency. This study contributes a novel integrated approach to formalizing a construction information model using a semiautomatic data integration approach, covering the information requirement and enables fluent data flow in the RCPSP solving process. Meanwhile, the work package-based information model is a successful attempt to introduce previouslygained knowledge into automatic schedule generation processes. Future work, such as extending the information model, creating new methods for RCPSP model generation, and data analytics, can bring new opportunities to apply more complex and intelligent methods in project scheduling and construction management.
Keywords: Information modeling | Data integration | Resource-constrained scheduling | Work package | Constraint programming | Optimization
A heuristic buffer sizing algorithm for implementing a renewable energy project
یک الگوریتم اندازه گیری بافر اکتشافی برای اجرای یک پروژه انرژی تجدید پذیر-2020
The swiftly growing wind farm projects together with the increasing uncertainty of these types of construction projects makes it more probable that projects will face delay. This research aims to introduce a heuristic algorithm to determine the sizes of project buffer and feeding buffers as well as dynamically control buffer consumption, named as Fuzzy Overlapping Buffer Management Algorithm (FOBMA). In this paper, the pentagonal fuzzy numbers were used to determine the appropriate amount of project activity resources. Also, an overlapping method was applied to obtain more realist activity durations. The FOBMA algorithm was compared to other algorithms using the data of 15 real-world wind farm projects as well as 15 randomly generated numerical examples. Moreover, the sensitivity analysis was conducted to validate the performance of the proposed algorithm. The findings demonstrate that the proposed FOBMA algorithm outperforms the other algorithms and yielded more realistic and shorter project duration.
Keywords: Construction project | Wind farm | Project scheduling | Buffer management | Buffer sizing and controlling algorithm | Pentagonal fuzzy numbers
An interval-stochastic programming based approach for a fully uncertain multi-objective and multi-mode resource investment project scheduling problem with an application to ERP project implementation
یک رویکرد مبتنی بر برنامه نویسی فاصله ای تصادفی برای یک هدف چندجانبه کاملاً نامشخص و برنامه زمانبندی پروژه سرمایه گذاری منابع چند حالته با برنامه ای برای اجرای پروژه ERP-2020
Most of the real-life project scheduling cases may involve different types of uncertainties simultane- ously such as randomness, fuzziness and dynamism. Based on this motivation, the present paper pro- poses a novel interval programming and chance constrained optimization based hybrid solution approach for a fully uncertain, multi-objective and multi-mode resource investment project scheduling problem (MRIPSP). The classical discrete-time binary integer programming formulation of the problem is extended by incorporating both the interval-valued and interval-stochastic project parameters as well as variables. In addition to the uncertain project parameters/inputs, the completion times of the activities which rep- resent the project schedule and the availabilities of the renewable project resources are also stated as uncertain project variables and represented by interval numbers. Then, the proposed interval-stochastic multi-mode resource investment project scheduling (IS-MRIPSP) model is converted into its crisp equiva- lent form by using the proposed approach. The proposed approach is also able to consider different types of project scheduling risks and produces more reliable and risk-free solutions according to the project manager’s attitude toward risks. Furthermore, in addition to the classical makespan objective, effective and efficient utilization of the renewable project resources, i.e., human resources, is also targeted. The efficiency and reliability factors of the human resources are also taken into consideration. In order to generate balanced project schedules which tradeoffbetween the project time and total human resource costs, compromise programming approach is adapted. Finally, in order to test the validity and practicality of the proposed approach, a real-life application is presented for an enterprise resource planning (ERP) implementation project scheduling problem of an international industrial software company.
Keywords: Resource investment project scheduling | Interval programming | Chance-constrained programming | Human resource allocation | ERP project management | Risk attitude