Best insertion algorithm for resource-constrained project scheduling problem

TL;DR

This paper introduces a heuristic approach for the resource-constrained project scheduling problem, combining randomized insertion and local search to improve schedule makespan, demonstrating strong performance on standard benchmarks.

Contribution

It proposes a novel heuristic combining randomized best insertion with local search for RCPSP, showing improved results over existing methods.

Findings

Achieved better makespan on PSPLIB instances

Effective combination of insertion and local search

Robust performance across test cases

Abstract

This paper considers heuristics for well known resource-constrained project scheduling problem (RCPSP). First a feasible schedule is constructed using randomized best insertion algorithm. The construction is followed by a local search where a new solution is generated as follows: first we randomly delete m activities from the list, which are then reinserted in the list in consecutive order. At the end of run, the schedule with the minimum makespan is selected. Experimental work shows very good results on standard test instances found in PSPLIB