Resource-constrained project scheduling: Notation, classification, models, and methods

https://www.econstor.eu/bitstream/10419/155418/1/manuskript_344.pdf

Serial and parallel resource-constrained project scheduling methods revisited: Theory and computation

http://www.om-db.wi.tum.de/psplib/files/KH-18-2-05.pdf

Experimental investigation of heuristics for resource-constrained project scheduling: An update

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.

Experimental Investigation of Heuristics for Resource-Constrained Project Scheduling: An Update

The paper describes an algorithm for the generation of a general class of precedence- and resource-constrained scheduling problems. Easy and hard instances for the single- and multi-mode resource-constrained project scheduling problem are benchmarked by using the state of the art (branch-and-bound-) procedures. The strong impact of the chosen parametric characterization of the problems is shown via an in-depth computational study. The results provided, demonstrate that the classical benchmark instances used by several researchers over decades belong to the subset of the very easy ones. In addition it is shown that hard instances, being far more smaller in size than presumed in the literature, may not be solved to optimality even within a huge amount of computational time.

https://www.econstor.eu/bitstream/10419/155395/1/manuskript_301.pdf

Characterization and generation of a general class of resource-constrained project scheduling problems: Easy and hard instances

This paper extends the field of heuristic algorithms for resource constrained scheduling problems in three important areas. First, an algorithm is introduced where the role of the heuristic scheduling urgency factor is expanded from one of solely determining the order in which activities are considered for scheduling at a given instant, to one of determining the combination of activities to be scheduled at this instant. Second, a new hybrid scheduling urgency factor capitalizing on the fact that this algorithm is sensitive to the absolute value rather than relative sequence of the urgency factors is introduced. Finally, a systematic approach to the evaluation of such algorithms is introduced. This includes the identification of relevant problem attributes and the adoption of evaluative concepts such as computational efficiency and analytic and systems effectiveness.

Heuristic Scheduling of Activities under Resource and Precedence Restrictions

In this age of modern era, the use of internet must be maximized. Yeah, internet will help us very much not only for important thing but also for daily activities. Many people now, from any level can use internet. The sources of internet connection can also be enjoyed in many places. As one of the benefits is to get the on-line simulation for decision making book, as the world window, as many people suggest.

Simulation for Decision Making

We first present a class of real-time scheduling problems and show that these can be formulated as semi-Markov decision problems. Then we discuss two practical difficulties in solving such problems. The first is that the resulting model requires a large amount of data that is difficult to obtain; the second is that the resulting model usually has a state space that is too large for analytic consideration. Finally, we present a non-intrusive ‘knowledge acquisition’ method that identifies the states and transition probabilities that an expert uses in solving these problems. This information is then used in the semi-Markov optimization problem. A circuit board production line is used to demonstrate the feasibility of this method. The size of the state space is reduced from 2035 states to 308 by an empirical procedure. An ‘optimal’ solution is derived based on the model with the reduced state space and estimated transition probabilities. The resulting schedule is significantly better than the one use...

Semi-markov decision models for real-time scheduling

Using a simple multiprocessor scheduling problem as a vehicle, we explore the behavior of tabu search algorithms using different tabu, local search and list management strategies. We found that random blocking of the tail of the tabu list always improved performance; but that the use of frequency-based penalties to discourage frequently selected moves did not. Hash coding without conflict resolution was an effective way to represent solutions on the tabu list. We also found that the most effective length of the tabu list depended on features of the algorithm being used, but not on the size and complexity of the problem being solved. The best combination of features included random blocking of the tabu list, tasks as tabus and a greedy local search. An algorithm using these features was found to outperform a recently published algorithm solving a similar problem.

/pdf/design-and-evaluation-of-tabu-search-algorithms-1kpxu8hq71.pdf

Arne Thesen

Papers

Heuristic Scheduling of Activities under Resource and Precedence Restrictions

Simulation for Decision Making

Semi-markov decision models for real-time scheduling

Design and Evaluation of Tabu Search Algorithms forMultiprocessor Scheduling

An expert scheduling system for material handling hoists