New representation to reduce the search space for the resource-constrained project scheduling problem

Abstract

Abstract. This paper describes a new representation for the solutions of the resource-constrained project scheduling problem (RCPSP) denoted Activity Set List. The most efficient heuristics for the problem use the activity list representation and the serial SGS method to construct the corresponding solution (schedule). The activity list may induce a search space of representations much larger then the space of schedules because the same schedule can correspond to many different activity list representations. We indicate how the activity set list representation can significantly reduce the search space, and how to move more efficiently through it. Furthermore, this new representation never excludes the optimal solution and it has many interesting properties. An evaluation of the search space reduction induced by this representation is made for the most used library of instances in the literature. The activity set list representation may be used to construct a new category of more efficient solution procedures for the problem.

A prediction model for ranking branch-and-bound procedures for the resource-constrained project scheduling problem

“…Klein & Scholl (1999) presented two meta-strategies for computing lower bounds for this challenging problem, and mentioned that the lack of strong lower bounds prevented the exact algorithms to solve large-sized problem instances. Moumene & Ferland (2008) mentioned that most exact algorithms from the literature are used to solve small problems with less than 60 activities, while heuristic procedures are alternatives to deal with larger problems. Inspired by these two research studies, Coelho & Vanhoucke (2018) recently implemented various lower bounds into different well-performing B&B procedures from the literature to solve the RCPSP, hoping that they could solve much bigger instances.…”

Modelling maintenance scheduling strategies for highway networks

“…As noted by Thomas and Salhi [ 26 ], the RCPSP is a NP-hard combinatorial optimization problem. The exact algorithms such as linear programming and branch-and-bound technique are feasible to solve this problem, but only effective for those small-sized problems with less than 60 activities [ 27 ]. For large-sized instances, it is proved that heuristic algorithms and more optimal solutions have better performance [ 28 ].…”

Improved discrete cuckoo search for the resource-constrained project scheduling problem

“…On the other hand, Moumene and Ferland (2008) proposed to decode solutions by using Activity Set List (ASL), which represents an ordered subset list of different non-empty activities. Each subset consists of a group of activities which share common characteristics, such as predecessors and successors; therefore, by using an ASL, the search space is significantly reduced.…”