Topic
Resource leveling
About: Resource leveling is a research topic. Over the lifetime, 602 publications have been published within this topic receiving 12787 citations.
Papers published on a yearly basis
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Papers
TL;DR: Computational results indicate that the procedures provide cost-effective optimal solutions for small problems and good heuristic solutions for larger problems, while simultaneously taking into account a variety of constraint types.
Abstract: This paper introduces methods for formulating and solving a general class of nonpreemptive resource-constrained project scheduling problems in which the duration of each job is a function of the resources committed to it. The approach is broad enough to permit the evaluation of numerous time or resource-based objective functions, while simultaneously taking into account a variety of constraint types. Typical of the objective functions permitted are minimize project duration, minimize project cost given performance payments and penalties, and minimize the consumption of a critical resource. Resources which may be considered include those which are limited on a period-to-period basis such as skilled labor, as well as those such as money, which are consumed and constrained over the life of the project. At the planning stage the user of this approach is permitted to identify several alternative ways, or modes, of accomplishing each job in the project. Each mode may have a different duration, reflecting the magnitude and mix of the resources allocated to it. At the scheduling phase, the procedure derives a solution which specifies how each job should be performed, that is, which mode should be selected, and when each mode should be scheduled. In order to make the presentation concrete, this paper focuses on two problems: given multiple resource restrictions, minimize project completion time, and minimize project cost. The latter problem is also known as the resource-constrained time-cost tradeoff problem.
Computational results indicate that the procedures provide cost-effective optimal solutions for small problems and good heuristic solutions for larger problems. The programmed solution algorithms are relatively simple and require only modest computing facilities, which permits them to be potentially useful scheduling tools for organizations having small computer systems.
483 citations
Book•
24 Jul 2012
TL;DR: The proposed Resource-Constrained Project Scheduling - Minimization of General Objective Functions incorporated branch-and-bound algorithms for resource investment, resource levelling, and resource renting problems, and additional types of shifts and sets of schedules.
Abstract: 1 Temporal Project Scheduling.- 1.1 Minimum and maximum time lags.- 1.2 Activity-on-node project networks.- 1.3 Temporal project scheduling computations.- 1.4 Orders in the set of activities.- 2 Resource-Constrained Project Scheduling - Minimization of Project Duration.- 2.1 Formulation of the problem.- 2.2 Cycle structures in activity-on-node project networks.- 2.3 Properties of the feasible region.- 2.3.1 Strict orders and order polyhedra.- 2.3.2 Forbidden sets and resolution of resource conflicts.- 2.4 Different types of shifts and sets of schedules.- 2.5 Branch-and-bound and truncated branch-and-bound methods.- 2.5.1 Enumeration scheme.- 2.5.2 Preprocessing.- 2.5.3 Lower bounds.- 2.5.4 Branch-and-bound algorithm.- 2.5.5 Truncated branch-and-bound methods.- 2.5.6 Alternative enumeration schemes.- 2.5.7 Alternative preprocessing and constraint propagation.- 2.5.8 Alternative lower bounds.- 2.6 Priority-rule methods.- 2.6.1 Direct method.- 2.6.2 Decomposition methods.- 2.6.3 Priority rules.- 2.6.4 Serial generation scheme.- 2.6.5 Parallel generation scheme.- 2.7 Schedule-improvement procedures.- 2.7.1 Genetic algorithm.- 2.7.2 Tabu search.- 2.8 Experimental performance analysis.- 2.8.1 Random generation of projects.- 2.8.2 Computational experience.- 2.9 Application to make-to-order production in manufacturing industry.- 2.10 Regular objective functions different from project duration.- 2.11 Calendarization.- 2.12 Project scheduling with cumulative resources.- 2.12.1 Discrete cumulative resources.- 2.12.2 Continuous cumulative resources.- 2.13 Project scheduling with synchronizing resources.- 2.14 Project scheduling with sequence-dependent changeover times.- 2.15 Multi-mode project scheduling problems.- 2.15.1 Problem formulation and basic properties.- 2.15.2 Solution methods.- 2.16 Application to batch production in process industries.- 2.16.1 Case study.- 2.16.2 Batching problem.- 2.16.3 Project scheduling model for batch scheduling.- 2.16.4 Solution procedure for batch scheduling.- 3 Resource-Constrained Project Scheduling - Minimization of General Objective Functions.- 3.1 Different objective functions.- 3.2 Additional types of shifts and sets of schedules.- 3.3 Classification of objective functions.- 3.3.1 Separable and resource-utilization dependent objective functions.- 3.3.2 Class 1 of regular objective functions.- 3.3.3 Class 2 of antiregular objective functions.- 3.3.4 Class 3 of convex objective functions.- 3.3.5 Class 4 of binary-monotone objective functions.- 3.3.6 Class 5 of quasiconcave objective functions.- 3.3.7 Class 6 of locally regular objective functions.- 3.3.8 Class 7 of locally quasiconcave objective functions.- 3.4 Time complexity of time-constrained project scheduling.- 3.5 Relaxation-based approach for function classes 1 to 5.- 3.5.1 General enumeration scheme.- 3.5.2 Branch-and-bound algorithm for the net present value problem.- 3.5.3 Branch-and-bound algorithm for the earliness-tardiness problem.- 3.6 Tree-based approach for function classes 6 and 7.- 3.6.1 General enumeration scheme.- 3.6.2 Branch-and-bound algorithms for resource investment, resource levelling, and resource renting problems.- 3.6.3 Experimental performance analysis.- 3.6.4 Alternative lower bounds.- 3.7 Priority-rule methods.- 3.7.1 Time-constrained project scheduling.- 3.7.2 Resource-constrained project scheduling.- 3.7.3 Experimental performance analysis.- 3.8 Schedule-improvement procedures.- 3.8.1 Neighborhoods for project scheduling problems.- 3.8.2 A tabu search procedure.- 3.9 Application to investment projects.- 3.9.1 Computation of the net present value function.- 3.9.2 Decision support.- 3.10 Hierarchical project planning.- References.- List of Symbols.- Three-Field Classification for Resource-Constrained Project Scheduling.
375 citations
TL;DR: A recurring problem in managing project activity involves the allocation of scarce resources to the individual activities comprising the project Resource conflict resolution decisions must be made whenever the concurrent demand for resources by the competing activities of a project exceeds resource availability.
Abstract: A recurring problem in managing project activity involves the allocation of scarce resources to the individual activities comprising the project Resource conflict resolution decisions must be made whenever the concurrent demand for resources by the competing activities of a project exceeds resource availability. When these resource conflict resolution decisions arise, project managers seek direction on which activities to schedule and which to delay in order that the resulting increase in project duration is the minimum that can be achieved with the given resource availabilities. The procedures examined in this paper are all designed to provide for this type of decision support. Each procedure examined is enumerative based, methodically searching the set of possible solutions in such a way that not all possibilities need be considered individually. The methods differ in the manner in which the tree representing partial schedules is generated and is saved, and differ in the methods which are used to identify and discard inferior partial schedules. Each procedure was found to be generally superior on a specific class of problems, and these classes are identified.
374 citations
Patent•
31 Aug 2004TL;DR: In this article, the authors describe a general resource management architecture that includes a resource manager and multiple resource providers that support one or more resource consumers such as a system component or application.
Abstract: Resource management architectures implemented in computer systems to manage resources are described. In one embodiment, a general architecture includes a resource manager and multiple resource providers that support one or more resource consumers such as a system component or application. Each provider is associated with a resource and acts as the manager for the resource when interfacing with the resource manager. The resource manager arbitrates access to the resources provided by the resource providers on behalf of the consumers. A policy manager sets various policies that are used by the resource manager to allocate resources. One policy is a priority-based policy that distinguishes among which applications and/or users have priority over others to use the resources. A resource consumer creates an “activity” at the resource manager and builds one or more “configurations” that describe various sets of preferred resources required to perform the activity. Each resource consumer can specify one or more configurations for each activity. If multiple configurations are specified, the resource consumer can rank them according to preference. This allows the resource consumers to be dynamically changed from one configuration to another as operating conditions change.
292 citations
TL;DR: In this paper, a multicriteria computational optimal scheduling model, which integrates the time/cost trade-off model, resource-limited model, and resource leveling model, is proposed.
Abstract: Resources for construction activities are limited in the real construction world. To avoid the waste and shortage of resources on a construction jobsite, scheduling must include resource allocation. A multicriteria computational optimal scheduling model, which integrates the time/cost trade-off model, resource-limited model, and resource leveling model, is proposed. A searching technique using genetic algorithms (GAs) is adopted in the model. Furthermore, the nondominated solutions are found by the multiple attribute decision-making method, technique for order preference by similarity to ideal solution. The model can effectively provide the optimal combination of construction durations, resource amounts, minimum direct project costs, and minimum project duration under the constraint of limited resources.
262 citations
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Performance Metrics
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| 2025 | 2 |
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| 2022 | 8 |
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| 2020 | 14 |