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Measuring schedule uncertainty for a stochastic resource-constrained project using scenario-based approach with utility-entropy decision model

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JOURNAL OF INDUSTRIAL AND PRODUCTION ENGINEERING 2016年第8期33卷 558-567页

作者： Tseng, Ching-Chih Ko, Po-Wen Dayeh Univ Dept Business Adm Changhua Taiwan JIT Boundary United Prod Inc Taoyuan Taiwan

The aim of this study is to propose a scenario-based approach with utility-entropy decision model to measure the uncertainty related to the evolution of a resource-constrained project scheduling problem with uncertain activity durations (a stochastic RCPSP). The approach consists of two stages. The first is to apply the proposal proposed by Tseng and Ko to convert a stochastic RCPSP into a full scenario tree. In stage two, we introduce the Expected Utility-Entropy (EU-E) decision model, a weighted linear average of expected utility and entropy, to establish an EU-E criterion. Then we apply the criterion to prune the worse branch(es) to lead a reduced scenario tree. Based on an illustrated example, it has been concluded that the reduced scenario tree by the EU-E criterion with larger trade-off coefficient. has less number of possible paths, less uncertainty, and lengthier expected project duration than that with smaller trade-off coefficient.. Thus, this has demonstrated that not only can the whole scenario during the course of a project be obtained, but also the uncertainty related to the evolution of a project can be measured.

关键词： resource-constrained project scheduling problem expected utility-entropy model scenario tree

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Dynamic Cooperative Interaction Strategy for Solving RCPSP by a Team of Agents 8th

Dynamic Cooperative Interaction Strategy for Solving RCPSP b...

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8th International Conference on Computational Collective Intelligence (ICCCI)

作者： Jedrzejowicz, Piotr Ratajczak-Ropel, Ewa Gdynia Maritime Univ Dept Informat Syst Morska 83 PL-81225 Gdynia Poland

ISBN: (纸本)9783319452425;9783319452432

In this paper a dynamic cooperative interaction strategy for the A-Team solving the resource-constrained project scheduling problem (RCPSP) is proposed and experimentally validated. The RCPSP belongs to the class of NP-hard optimization problems. To solve this problem a team of asynchronous agents (A-Team) has been implemented using multiagent environment. An A-Team consist of the set of objects including multiple optimization agents, manager agents and the common memory which through interactions produce solutions of hard optimization problems. In this paper the dynamic cooperative interaction strategy is proposed. The strategy supervises cooperation between agents and the common memory. To validate the proposed approach the preliminary computational experiment has been carried out.

关键词： resource-constrained project scheduling problem RCPSP Optimization Agent A-Team

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An Extension of a Dynamic Heuristic Solution for Solving a Multi-Objective Optimization problem in the Defense Industry 3rd

An Extension of a Dynamic Heuristic Solution for Solving a M...

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3rd International Conference on Optimization, Learning Algorithms and Applications (OL2A)

作者： Ninpan, Khwansiri Kondratenko, Kirill Huang, Shuzhang Plancon, Alexandra Aumont, Arthur Artaud, Lucas Baker, Mouna Roumili, Emir Vitillo, Francesco Bechet, Lies Benmiloud Plana, Robert Assystem Digital Excellence Ctr Courbevoie France Assystem Technol & Innovat Courbevoie France

ISBN: (纸本)9783031530241;9783031530258

project scheduling in a real-life scenario often involves multiple-criteria decision-making in which no single solution exists. To solve such a problem, a multi-objective optimization method has been applied to define the satisfying trade-off between different criteria. In this paper, we focus on a specific use case in the defense industry in which the overall mission is to generate a maintenance plan for the transfer operations of power grid consumers to the new service area. The project objectives include restricting the outage duration during transfer operations, grouping operations concerning the proximity between them, moderating the allocation of supporting resource, and regulating human resources intervention outside business hours. To solve this problem, we propose a combination of heuristic approaches starting by defining a sequence of activities based on their complexities to be scheduled. Concerning the obtained order, a serial-schedule generation scheme (S-SGS) is then implemented by iterating through each activity to define the best time period to proceed the operation in accordance with project's multiple objectives. Finally, the output is transferred to our existing parallel scheme-based solver, Optimizio, to finally justify the project planning. The proposed S-SGS solution provides a feasible schedule of 110 transfer operations in 2 s with solution evaluation analysis and information of a Pareto frontier in approximately 15min. The set of Pareto optimal solutions allows the expert to explore potential trade-offs between criteria. Together with a fast execution time of the algorithms that benefits a multi-scenario simulation, our tool demonstrates a potential capacity to get the optimum outcome of the multi-objective optimization project.

关键词： Serial-Schedule Generation Scheme Multi-Objective Programming Heuristic Algorithms resource-constrained project scheduling problem

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A holistic analysis of maritime logistics process in fuzzy environment in terms of business process management

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BUSINESS PROCESS MANAGEMENT JOURNAL 2023年第4期29卷 1116-1158页

作者： Akan, Ercan Iskenderun Tech Univ Dept Maritime Transportat Management Engn Iskenderun Turkiye

PurposeThe aim of this study is to provide a holistic analysis of all possible maritime business logistics processes related to import and export shipments in a fuzzy environment through a case study of a maritime logistics company based on the as-is and to-be models within business process management (BPM).Design/methodology/approachThe analyses considered the following perspectives: (i) in the stage of the process identification, the definition of the problem was carried out;(ii) in the stage of the process discovery, ocean department was divided into ocean export/import operation departments;ocean export/import operation were divided into freight collect/prepaid operation processes;ocean export/import logistics activity groups were broken down into sub-activities for freight collect/prepaid operation;the logistics activity groups and their sub-activities were defined;each sub-activity as either operation or documentation process group was classified;the durations of sub-activities were evaluated by decision-makers (DMs) as fuzzy sets (FSs);the monthly total jobs activities were estimated by DMs as FSs;the applied to monthly jobs activities of total shipments were estimated by DMs as FSs;the durations of each sub-activities were aggregated;the duration of the logistics activity groups and the sub-activities for per job were calculated;the cumulative workload of logistics activity groups and sub-activities were calculated;the duration of sub-activities for per job as operation or documentation departments were calculated, (iii) in the stage of the process analysis, cumulative ocean export/import workload as operation or documentation for freight collect/prepaid were calculated;duration of activity groups and sub-activities for per job as operation or documentation were calculated;cumulative workload activity groups and sub-activities as operation or documentation were calculated, (iv) in the stage of the process redesign, cumulative workload, process cycle time as

关键词： Maritime logistics Business process analysis Business process management Process redesign Fuzzy sets Critical path method resource-constrained project scheduling problem

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Efficient Adaptive Implementation of the Serial Schedule Generation Scheme Using Preprocessing and Bloom Filters 11th

Efficient Adaptive Implementation of the Serial Schedule Gen...

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11th International Conference on Learning and Intelligent Optimization (LION)

作者： Karapetyan, Daniel Vernitski, Alexei Univ Essex Inst Analyt & Data Sci Colchester Essex England Univ Essex Dept Math Sci Colchester Essex England

ISBN: (纸本)9783319694047;9783319694030

The majority of scheduling metaheuristics use indirect representation of solutions as a way to efficiently explore the search space. Thus, a crucial part of such metaheuristics is a "schedule generation scheme" - procedure translating the indirect solution representation into a schedule. Schedule generation scheme is used every time a new candidate solution needs to be evaluated. Being relatively slow, it eats up most of the running time of the metaheuristic and, thus, its speed plays significant role in performance of the metaheuristic. Despite its importance, little attention has been paid in the literature to efficient implementation of schedule generation schemes. We give detailed description of serial schedule generation scheme, including new improvements, and propose a new approach for speeding it up, by using Bloom filters. The results are further strengthened by automated control of parameters. Finally, we employ online algorithm selection to dynamically choose which of the two implementations to use. This hybrid approach significantly outperforms conventional implementation on a wide range of instances.

关键词： resource-constrained project scheduling problem Serial schedule generation scheme Bloom filters Online algorithm selection

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Dynamic scheduling model for the construction industry

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BUILT ENVIRONMENT project AND ASSET MANAGEMENT 2020年第3期10卷 313-330页

作者： Fahmy, Amer Hassan, Tarek Bassioni, Hesham McCaffer, Ronald CCC TAV JV Project Controls Dept Muscat Oman Loughborough Univ Sch Architecture Bldg & Civil Engn Loughborough Leics England Arab Acad Sci Technol & Maritime Transport Construct & Bldg Engn Dept Alexandria Egypt

Purpose Basic project control through traditional methods is not sufficient to manage the majority of real-time events in most construction projects. The purpose of this paper is to propose a Dynamic scheduling (DS) model that utilizes multi-objective optimization of cost, time, resources and cash flow, throughout project construction. Design/methodology/approach Upon reviewing the topic of DS, a worldwide internet survey with 364 respondents was conducted to define end-user requirements. The model was formulated and solution algorithms discussed. Verification was reported using predefined problem sets and a real-life case. Validation was performed via feedback from industry experts. Findings The need for multi-objective dynamic software optimization of construction schedules and the ability to choose among a set of optimal alternatives were highlighted. Model verification through well-known test cases and a real-life project case study showed that the model successfully achieved the required dynamic functionality whether under the small solved example or under the complex case study. The model was validated for practicality, optimization of various DS schedule quality gates, ease of use and software integration with contemporary project management practices. Practical implications Optimized real-time scheduling can provide better resources management including labor utilization and cost efficiency. Furthermore, DS contributes to optimum materials procurement, thus minimizing waste. Social implications Optimized real-time scheduling can provide better resources management including labor utilization and cost efficiency. Furthermore, DS contributes to optimum materials procurement, thus minimizing waste. Originality/value The paper illustrates the importance of DS in construction, identifies the user needs and overviews the development, verification and validation of a model that supports the generation of high-quality schedules beneficial to large-scale projects.

关键词： scheduling resource management Multi-objective optimization Dynamic scheduling Particle swarm resource-constrained project scheduling problem

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Proactive and Reactive Risk-Aware project scheduling

Proactive and Reactive Risk-Aware Project Scheduling

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IEEE Symposium on Computational Intelligence for Human-Like Intelligence (CIHLI)

作者： Waledzik, Karol Mandziuk, Jacek Zadrozny, Slawomir Warsaw Univ Technol Fac Math & Informat Sci Koszykowa 75 PL-00662 Warsaw Poland Polish Acad Sci Syst Res Inst PL-01447 Warsaw Poland

ISBN: (纸本)9781479945061

In order to create a test-bed for Computational Intelligence (CI) methods dealing with complex, non-deterministic and dynamic environments we propose a definition of a new class of problems, based on the real-world task of project scheduling and executing with risk management. Therefore, we define Risk-Aware project scheduling problem (RAPSP) as a (significant) modification of the resource-constrained project scheduling problem (RCPSP). We argue that this task is, considering its daunting complexity, sometimes surprisingly well solved by experienced humans, relying both on tools and their intuition. We speculate that a CI-based solver for RAPSP should also employ multiple cognitively-inspired approaches to the problem and we propose three such solvers of varying complexity and inspiration. Their efficacy comparison is in line with our expectations and supports our claims.

关键词： optimisation problem solving project management resource allocation risk management scheduling CI methods CI-based solver RAPSP RCPSP cognitively-inspired approach computational intelligence methods dynamic environments nondeterministic environments proactive risk-aware project scheduling reactive risk-aware project scheduling resource-constrained project scheduling problem risk-aware project scheduling problem Algorithm design and analysis Complexity theory Law Monte Carlo methods Risk management Schedules Risk Management Algorithm design and analysis Complexity theory Monte Carlo technique management of resources project management problem solving resource utilization Artificial Intelligence Computational intelligence New classes

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A Pointer-based Discrete Differential Evolution

A Pointer-based Discrete Differential Evolution

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IEEE Congress on Evolutionary Computation

作者： Dong, Yun Guo, Qingxin Tang, Lixin Northeastern Univ Logist Inst Shenyang 110819 Peoples R China

ISBN: (纸本)9781479904549;9781479904532

To solve the discrete optimization problem, the traditional continuous differential evolution (DE) algorithm has to be modified in individual representation or evolution strategy. Inspired from a pair of reciprocal operators (pointer and address-of) in computer programming language, a novel pointer-based discrete differential evolution (PDDE) is presented in this paper. Making use of the permutation of integers as the individual representation, PDDE redefines the addition and subtraction operations of traditional DE to construct discrete mutation operator. In addition, the scaling factor and crossover probability factor are redefined to fit the discrete operation. The performance of PDDE is evaluated through extensively experiments on comparing general searching ability and solving resource-constrained project scheduling problem. The computational results show that the proposed PDDE is efficient.

关键词： differential evolution discrete optimization pointer-based mutation resource-constrained project scheduling problem

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Visual Planning and scheduling of Industrial projects With Spatial Factors

Visual Planning and Scheduling of Industrial Projects With S...

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20th ISPE International Conference on Concurrent Engineering

作者： Semenov, Vitaly Anichkin, Anton Morozov, Sergey Tarlapan, Oleg Zolotov, Vladislav Russian Acad Sci Inst Syst Programming 25 Alexander Solzhenitsyn St Moscow 109004 Russia

ISBN: (纸本)9781614993025;9781614993018

With the increasing complexity and scale of industrial projects the need of comprehensive and trustworthy methods for planning and scheduling becomes more and more apparent. Being implemented in recent project management systems, the traditional methods aid in project scheduling based on activity durations, precedence relationships, explicit timing constraints, and resource limits all assumed by resource-constrained project scheduling problem (RCPSP). However, the methods have many shortcomings for the industrial projects where spatial factors play critically important role. The objective of this paper is to present an advanced Visual scheduling Method (VSM) for solving Generally constrained project scheduling problem (GCPSP) that extends the classical RCPSP statement by taking into account additional spatial factors such as product element collisions, missing of supporting neighbouring elements, workspace congestion. In the paper we provide a holistic framework of the method as well as illustrate how feasible project schedules can be generated under complex spatio-temporal constraints in highly automatic and visually interpretable way. A software implementation of the method and its prospects for application in industrial practice are discussed too.

关键词： Planning and scheduling resource-constrained project scheduling problem 4D modelling spatio-temporal validation

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Optimization of the short-term labor and task scheduling in the maintenance of regional trains

Optimization of the short-term labor and task scheduling in ...

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作者： van Leeuwen, Anouk Delft University of Technology

学位级别：硕士

The Dutch Railways (NS) is the Dutch national passenger railway operator. They own rolling stock that has to be maintained regularly. One of the maintenance facilities executing regular maintenance on regional trains is the maintenance department (OB) in Leidschendam. The aim of this project is to develop a framework for optimizing the productivity in the combined labor and task scheduling in the maintenance of regional trains on a daily perspective to increase the delivery reliability. A mathematical model has been developed based on the resource-constrained project scheduling problem. To solve the model a hybrid method combining a genetic algorithm and an annealing-like search heuristic is proposed. Three experiments are performed using real data. During the fist experiment the schedule performance of the algorithm is compared with the performance of the schedules generated by the planners of the OB. The second experiment evaluates different qualification distributions for the available workforce. During the last experiment, the effect of the tardiness cost as introduced in this research is evaluated. The experiments show that the scheduled productivity is increased with an average of 18% per day when the algorithm is used and on average 3 more train units are completely scheduled per day.

关键词： Rolling Stock Maintenance scheduling resource-constrained project scheduling problem Hybrid Heuristics Genetic Algorithm Simulated Annealing

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