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 ...

This paper describes a new technique for solving the duration minimization in a resourceconstrained network. It is based on a transformation of the resource-constrained project scheduling problem (RCPSP) to a sequence of (multi)knapsack problem (MKP) solutions. In the first part, three deterministic approaches are summarized and their time complexity is discussed. Due to the combinatorial natur...

This paper focuses on estimating maximum resource loads in ResourceConstrained Project Scheduling Problem (RCPSP). We examine a variant of vector sum problem with fractions: considering preemptions allowed, determine what part of each of n jobs should be accomplished in order to minimize sum of squares of non-consumed amounts of resources, taking into account the resource constraints along with...

The integration of machine learning methods into meta-heuristic search techniques is currently an important topic in the field of combinatorial optimisation. It is often referred to as intelligent optimisation [1]. Learning has the potential of helping the search process in several ways. Searching for instance, can become more generic when online learning and automation mechanisms tune the crit...

In the Capacitated Open Pit Mining Problem, we consider the sequential extraction of blocks in order to maximize the total discounted profit under an extraction capacity during each period of the horizon. We propose a formulation closely related to the Resource-Constrained Project Scheduling Problem (RCPSP) where the genotype representation of the solution is based on a priority value encoding....

In this paper, we have proposed new algorithms for the problem of predictive production scheduling, with the Resource-Constrained Project Scheduling Problem (RCPSP). Those algorithms are adjusted for making robust the activity sequences characterised by specific unsurpassable times of completion of particular tasks related to milestones. The calculation procedures presented here provide protect...

Scheduling problems considered in the literature are often static (activities are known in advance and constraints are fixed). However, every real-life schedule is subject to unexpected events. In these cases, a new solution is needed in a preferably short time and as close as possible to the current solution. In this paper, we present an exact approach for solving dynamic Resource-Constrained ...

A P system for resource-constrained project scheduling problem(RCPSP) based on serial schedule generation scheme is proposed in this paper to provide new ideas for parallel solutions in today’s big data environment. Because P system has great parallelism, it could solve hard problems, typically NP-complete problems, in polynomial time. We use membrane to conduct the whole process of computation...

This paper proposes a Hybrid Genetic Algorithm (HGA) for the Resource Constrained Project Scheduling Problem (RCPSP). Resources are renewable and there is a unique way to perform the activities. This work employs Genetics Algorithms (GA) and Hybrid Genetic Algorithms to schedule project activities to minimize makespan subject to precedence constraints and resources availability. The algorithms ...