Comparing optimization modeling approaches for the multi-mode resource-constrained multi-project scheduling problem
06 Apr 2020-Engineering, Construction and Architectural Management (Emerald Publishing Limited)-Vol. 27, Iss: 4, pp 893-916
TL;DR: In this paper, the authors compare two approaches for multi-mode resource-constrained project scheduling in a multi-project environment: the single-project approach (portfolio optimization) and the multiannual approach (each project is optimized individually, and then heuristic rules are used to satisfy the portfolio constraint).
Abstract: Construction firms keep minimal resources to maintain productive working capital. Hence, resources are constrained and have to be shared among multiple projects in an organization. Optimal allocation of resources is a key challenge in such situations. Several approaches and heuristics have been proposed for this task. The purpose of this paper is to compare two approaches for multi-mode resource-constrained project scheduling in a multi-project environment. These are the single-project approach (portfolio optimization) and the multi-project approach (each project is optimized individually, and then heuristic rules are used to satisfy the portfolio constraint).,A direct search algorithm called Probabilistic Global Search Lausanne is used for schedule optimization. Multiple solutions are generated that achieve different trade-offs among the three criteria, namely, time, cost and quality. Good compromise solutions among these are identified using a multi-criteria decision making method, Relaxed Restricted Pareto Version 4. The solutions obtained using the single-project and multi-project approaches are compared in order to evaluate their advantages and disadvantages. Data from two sources are used for the evaluation: modified multi-mode resource-constrained project scheduling problem data sets from the project scheduling problem library (PSPLIB) and three real case study projects in India.,Computational results prove the superiority of the single-project approach over heuristic priority rules (multi-project approach). The single-project approach identifies better solutions compared to the multi-project approach. However, the multi-project approach involves fewer optimization variables and is faster in execution.,It is feasible to adopt the single-project approach in practice; realistic resource constraints can be incorporated in a multi-objective optimization formulation; and good compromise solutions that achieve acceptable trade-offs among the conflicting objectives can be identified.,An integer programming model was developed in this research to optimize the multiple objectives in a multi-project environment considering explicit resource constraints and maximum daily costs constraints. This model was used to compare the performance of the two multi-project environment approaches. Unlike existing work in this area, the model used to predict the quality of activity execution modes is based on data collected from real construction projects.
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TL;DR: The findings show that multiple criteria decision analysis is the most used method for decision support in building construction and that the construction phase is themost addressed phase within the relevant existing works.
Abstract: Decision making is a relevant task in the building construction sector, and various systems and methods for decision support are emerging. By means of a systematic literature review, this article identifies the methods for decision making in building construction and the lifecycle phases for which decision support systems are proposed. The selected articles are analyzed and grouped according to the adopted decision-making methods and the defined lifecycle phases. The findings show that multiple criteria decision analysis is the most used method for decision support in building construction and that the construction phase is the most addressed phase within the relevant existing works. The findings related to the construction phase are further refined by grouping the articles into application areas and by reviewing in detail the proposed methods therein. The scarce availability of data and project cases is identified as the most common barrier for the successful development and implementation of decision support systems in the building construction sector. This work provides a basis for scientists and practitioners for identifying suitable methods for decision-making support in a specific lifecycle phase of a building.
20 citations
Cites background from "Comparing optimization modeling app..."
...• Supply chain management and material procurement [71,75,86,90,91,94]; • Construction contracts and bidding [73,74,76,81,97]; • Equipment and logistics [72,83,89,99]; • Hazard analysis and safety planning [78,92,95,98]; • Project duration and scheduling [70,79,82,85]; • Optimization, performance and management of modular construction projects [69,80,84,96]; • Making decisions regarding overseas construction projects for companies [77]; • Environmental assessment and optimization [87]; • Software selection for the execution phase [88]; • Entropic risk analysis [93]....
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...Supply chain and materials [71,75] [86,90,91] [94] Contracts and bidding [73,74] [76] [81] [97] Equipment and logistics [72] [83,89] [99] Hazards and safety [78] [92] [95,98] Scheduling and duration [70] [79] [82] [85] Modular construction [69] [80] [84] [96] Other applications [77] [87,88,93] Buildings 2020, 10, x FOR PEER REVIEW 11 of 19...
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TL;DR: The Resource-Constrained Multi-Project Scheduling Problem (RCMPSP) as mentioned in this paper consists of assigning start times to jobs corresponding to two or more projects that must be executed simultaneously while respecting the precedence between jobs and limited resources.
Abstract: Project Management is becoming increasingly crucial in competitive environments such as manufacturing and the service industries. The Resource-Constrained Multi-Project Scheduling Problem (RCMPSP) consists of assigning start times to jobs corresponding to two or more projects that must be executed simultaneously while respecting the precedence between jobs and limited resources. The existing rise in the study of the RCMPSP resulted in numerous works on the topic while proposing different problem features. This research analyzes different variants of the problem based on aspects related to jobs, projects, relationships, resources, and time management. Moreover, based on the problem variants considered in the collected works, a taxonomy allowing (i) the identification and positioning of each RCMPSP variant and (ii) the analysis of the current state-of-the-art of the problem is proposed. In addition, the solution methods proposed to solve RCMPSPs are classified and analyzed, together with the benchmarks used to validate such approaches. Finally, this review paper discusses the RCMPSP connection to practice and provides future research opportunities in light of recent advances.
5 citations
TL;DR: In this paper, the authors compared 17 heuristic priority rules and found that the minimum late finish time rule generated the shortest predicted project duration when used in parallel resource allocation, whereas the "minimum late start time", "minimum early start time", and the "highest rank of positional weight 2" rules performed best in serial resource allocation.
Abstract: Resource-constrained project scheduling (RCPS) aims to minimize project duration under limited resource availabilities. The heuristic methods that are often used to solve the RCPS problem make use of different priority rules. The comparative merits of different priority rules have not been discussed in the literature in sufficient detail. This study is a response to this research gap. It compares 17 heuristic priority rules and seeks the best performing heuristic priority rule. This is the first study ever that compares heuristic priority rules by considering combinations of variations in (1) resource allocation procedures, (2) number of activities, (3) number of resource constraints, and (4) resource supply levels. The objective is to understand the relative merits of heuristic rules used in solving the RCPS problem. The findings indicate that the “minimum late finish time” rule generates the shortest predicted project duration when used in parallel resource allocation, whereas the “minimum late start time”, “minimum late finish time”, and the “highest rank of positional weight 2” rules perform best in serial resource allocation. It was also found that parallel resource allocation is slightly superior to serial resource allocation in most instances.
2 citations
TL;DR: In this article , the optimal allocation and utilization of key resources of the enterprise in collaborative innovation projects is studied from the perspective of repeated games of the project participants, and some suggestions are put forward to promote cooperation and improve project performance.
Abstract: The rational allocation and utilization of key corporate resources is the key to the success of collaborative innovation projects. Finding an optimal strategy for the allocation and utilization of key resources is of great significance for promoting the smooth progress of cooperative both innovation parties and increasing project returns. Therefore, from the perspective of the repeated games of the project participants, this article studies the optimal allocation and utilization of key resources of the enterprise in collaborative innovation projects. In this study, nine scenarios and eighteen strategic combinations of resources allocation and utilization by collaborative innovation partners are explored. Explicit expressions for the components of sixteen equilibrium points in terms of parameters are derived. Among these equilibrium points, four stable solutions are determined. These stable solutions correspond to the optimal strategies for enterprises allocating key resources and A&R parties to use these resources in different scenarios, and these strategies enable partners to maximize their interests. On this basis, some suggestions are put forward to promote cooperation and improve project performance.
2 citations
TL;DR: In this paper , the authors investigated the factors influencing project portfolio benefits (PPBs) while considering the synergistic effect among factors to provide guidelines for benefits management and found that factors that share the same subgroup are more likely to have a synergistic advantage advantage, which leads to an increase in PPBs.
Abstract: PurposeRealizing project portfolio benefits (PPBs) is considered a key challenge faced by enterprises. This challenge can largely be attributed to an unclear understanding of the factors influencing PPBs. However, synergistic relationships create complexity for the management of influencing factors. In response to this dilemma, the objective of this study is to quantitatively investigate the factors influencing PPBs while considering the synergistic effect among factors to provide guidelines for benefits management.Design/methodology/approachThrough an integration of the synergy degree of the composite system model and social network analysis (SNA), a refined model is proposed to explore the factors influencing PPBs. First, a list that includes financial and nonfinancial influencing factors is clarified. Then, the corresponding network links, which represent the synergistic relationships among the factors, are innovatively assessed based on the synergy degree of the composite system. Finally, the influencing factor network is analyzed using both individual and overall indicators of SNA.FindingsThe resulting evidence demonstrates that four critical influencing factors exist, namely, “project managers,” “purchasers,” “development capacity” and “tangible resources.” These factors are relatively important and should be prioritized. Furthermore, the factors are divided into three subgroups: participant, resource and governmental factors. A general observation from the results is that factors that share the same subgroup are more likely to have a synergistic effect advantage, which leads to an increase in PPBs.Originality/valueThe value of this paper lies in its proposition of a quantitative model that can be used to measure and analyze the factors influencing PPBs with synergy considerations. This research contributes to the body of knowledge on benefits management by linking synergy with PPBs. It presents new insights for managers on how PPBs may be effectively managed and promoted from the perspective of influencing factors.
1 citations
References
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TL;DR: An overview over various extensions of the basic RCPSP, including popular variants and extensions such as multiple modes, minimal and maximal time lags, and net present value-based objectives, is given.
Abstract: The resource-constrained project scheduling problem (RCPSP) consists of activities that must be scheduled subject to precedence and resource constraints such that the makespan is minimized. It has become a well-known standard problem in the context of project scheduling which has attracted numerous researchers who developed both exact and heuristic scheduling procedures. However, it is a rather basic model with assumptions that are too restrictive for many practical applications. Consequently, various extensions of the basic RCPSP have been developed. This paper gives an overview over these extensions. The extensions are classified according to the structure of the RCPSP. We summarize generalizations of the activity concept, of the precedence relations and of the resource constraints. Alternative objectives and approaches for scheduling multiple projects are discussed as well. In addition to popular variants and extensions such as multiple modes, minimal and maximal time lags, and net present value-based objectives, the paper also provides a survey of many less known concepts.
856 citations
TL;DR: In this paper, a survey of heuristics for resource-constrained project scheduling problem (RCPSP) is presented, which provides an update of our survey which was published in 2000.
Abstract: This paper considers heuristics for the well-known resource-constrained project scheduling problem (RCPSP). It provides an update of our survey which was published in 2000. We summarize and categorize a large number of heuristics that have recently been proposed in the literature. Most of these heuristics are then evaluated in a computational study and compared on the basis of our standardized experimental design. Based on the computational results we discuss features of good heuristics. The paper closes with some remarks on our test design and a summary of the recent developments in research on heuristics for the RCPSP.
673 citations
01 Jan 2004
TL;DR: In this paper, a survey of heuristics for resource-constrained project scheduling problem (RCPSP) is presented, which provides an update of our survey which was published in 2000.
Abstract: This paper considers heuristics for the well-known resource-constrained project scheduling problem (RCPSP). It provides an update of our survey which was published in 2000. We summarize and categorize a large number of heuristics that have recently been proposed in the literature. Most of these heuristics are then evaluated in a computational study and compared on the basis of our standardized experimental design. Based on the computational results we discuss features of good heuristics. The paper closes with some remarks on our test design and a summary of the recent developments in research on heuristics for the RCPSP.
661 citations
TL;DR: An algorithm based on the principles of GAs for construction time-cost trade-off optimization and a computer program that can execute the algorithm efficiently are presented.
Abstract: Time-cost trade-off analysis is one of the most important aspects of construction project planning and control. There are trade-offs between time and cost to complete the activities of a project; in general, the less expensive the resources used, the longer it takes to complete an activity. Using critical path method (CPM), the overall project cost can be reduced by using less expensive resources for noncritical activities without impacting the project duration. Existing methods for time-cost trade-off analysis focus on using heuristics or mathematical programming. These methods, however, are not efficient enough to solve large-scale CPM networks (hundreds of activities or more). Analogous to natural selection and genetics in reproduction, genetic algorithms (GAs) have been successfully adopted to solve many science and engineering problems and have proven to be an efficient means for searching optimal solutions in a large problem domain. This paper presents: (1) an algorithm based on the principles of GAs for construction time-cost trade-off optimization; and (2) a computer program that can execute the algorithm efficiently.
441 citations
TL;DR: This paper presents a genetic algorithm for the resource constrained multi-project scheduling problem based on random keys that builds parameterized active schedules based on priorities, delay times, and release dates defined by the genetic algorithm.
Abstract: This paper presents a genetic algorithm for the resource constrained multi-project scheduling problem. The chromosome representation of the problem is based on random keys. The schedules are constructed using a heuristic that builds parameterized active schedules based on priorities, delay times, and release dates defined by the genetic algorithm. The approach is tested on a set of randomly generated problems. The computational results validate the effectiveness of the proposed algorithm.
341 citations