A min-flow algorithm for Minimal Critical Set detection in Resource Constrained Project Scheduling

AbstractWe propose a min-flow algorithm for detecting Minimal Critical Sets (MCS) in Resource Constrained Project Scheduling Problems (RCPSP). The MCS detection is a fundamental step in the Precedence Constraint Posting method (PCP), one of the most successful approaches for the RCPSP. The proposed approach is considerably simpler compared to existing flow based MCS detection procedures and has better scalability compared to enumeration- and envelope-based ones, while still providing good quality Critical Sets. The method is suitable for problem variants with generalized precedence relations or uncertain/variable durations

Stability and resource allocation in project planning.

The majority of resource-constrained project scheduling efforts assumes perfect information about the scheduling problem to be solved and a static deterministic environment within which the pre-computed baseline schedule is executed. In reality, project activities are subject to considerable uncertainty, which generally leads to numerous schedule disruptions. In this paper, we present a resource allocation model that protects a given baseline schedule against activity duration variability. A branch-and-bound algorithm is developed that solves the proposed resource allocation problem. We report on computational results obtained on a set of benchmark problems.Constraint satisfaction; Information; Model; Planning; Problems; Project management; Project planning; Project scheduling; Resource allocati; Scheduling; Stability; Uncertainty; Variability;

Models for robust resource allocation in project scheduling.

The vast majority of resource-constrained project scheduling efforts assumes complete information about the scheduling problem to be solved and a static deterministic environment within which the pre-computed baseline schedule will be executed. In reality, however, project activities are subject to considerable uncertainty which generally leads to numerous schedule disruptions. In this paper, we present a resource allocation model that protects the makespan of a given baseline schedule against activity duration variability. A branch-and-bound algorithm is developed that solves the proposed robust resource allocation problem in exact and approximate formulations. The procedure relies on constraint propagation during its search. We report on computational results obtained on a set of benchmark problems.Model; Resource allocation; Scheduling;

Multi-Objective Multi-mode Time-Cost Tradeoff modeling in Construction Projects Considering Productivity Improvement

In today's construction industry, poor performance often arises due to various factors related to time, finances, and quality. These factors frequently lead to project delays and resource losses, particularly in terms of financial resources. This research addresses the Multimode Resource-Constrained Project Scheduling Problem (MRCPSP), a real-world challenge that takes into account the time value of money and project payment planning. In this context, project activities exhibit discrete cost profiles under different execution conditions and can be carried out in multiple ways. This paper aims to achieve two primary objectives: minimizing the net present value of project costs and project completion times while simultaneously improving the project's productivity index. To accomplish this, a mathematical programming model based on certain assumptions is proposed. Several test cases are designed, and they are rigorously evaluated using the methodology outlined in this paper to validate the modeling approach. Recognizing the NP-hard nature of this problem, a multi-objective genetic algorithm capable of solving large-scale instances is developed. Finally, the effectiveness of the proposed solution is assessed by comparing it to the performance of the NSGA-II algorithm using well-established efficiency metrics. Results demonstrate the superior performance of the algorithm introduced in this study.Comment: 40 pages, 20 figures, 7 table

Working Notes from the 1992 AAAI Spring Symposium on Practical Approaches to Scheduling and Planning

The symposium presented issues involved in the development of scheduling systems that can deal with resource and time limitations. To qualify, a system must be implemented and tested to some degree on non-trivial problems (ideally, on real-world problems). However, a system need not be fully deployed to qualify. Systems that schedule actions in terms of metric time constraints typically represent and reason about an external numeric clock or calendar and can be contrasted with those systems that represent time purely symbolically. The following topics are discussed: integrating planning and scheduling; integrating symbolic goals and numerical utilities; managing uncertainty; incremental rescheduling; managing limited computation time; anytime scheduling and planning algorithms, systems; dependency analysis and schedule reuse; management of schedule and plan execution; and incorporation of discrete event techniques

Development and demonstration of an on-board mission planner for helicopters

Mission management tasks can be distributed within a planning hierarchy, where each level of the hierarchy addresses a scope of action, and associated time scale or planning horizon, and requirements for plan generation response time. The current work is focused on the far-field planning subproblem, with a scope and planning horizon encompassing the entire mission and with a response time required to be about two minutes. The far-feld planning problem is posed as a constrained optimization problem and algorithms and structural organizations are proposed for the solution. Algorithms are implemented in a developmental environment, and performance is assessed with respect to optimality and feasibility for the intended application and in comparison with alternative algorithms. This is done for the three major components of far-field planning: goal planning, waypoint path planning, and timeline management. It appears feasible to meet performance requirements on a 10 Mips flyable processor (dedicated to far-field planning) using a heuristically-guided simulated annealing technique for the goal planner, a modified A* search for the waypoint path planner, and a speed scheduling technique developed for this project