A greedy heuristic approach for the project scheduling with labour allocation problem

Responding to the growing need of generating a robust project scheduling, in this article we present a greedy algorithm to generate the project baseline schedule. The robustness achieved by integrating two dimensions of the human resources flexibilities. The first is the operators’ polyvalence, i.e. each operator has one or more secondary skill(s) beside his principal one, his mastering level being characterized by a factor we call “efficiency”. The second refers to the working time modulation, i.e. the workers have a flexible time-table that may vary on a daily or weekly basis respecting annualized working strategy. Moreover, the activity processing time is a non-increasing function of the number of workforce allocated to create it, also of their heterogynous working efficiencies. This modelling approach has led to a nonlinear optimization model with mixed variables. We present: the problem under study, the greedy algorithm used to solve it, and then results in comparison with those of the genetic algorithms

Decision-based genetic algorithms for solving multi-period project scheduling with dynamically experienced workforce

The importance of the flexibility of resources increased rapidly with the turbulent changes in the industrial context, to meet the customers’ requirements. Among all resources, the most important and considered as the hardest to manage are human resources, in reasons of availability and/or conventions. In this article, we present an approach to solve project scheduling with multi-period human resources allocation taking into account two flexibility levers. The first is the annual hours and working time regulation, and the second is the actors’ multi-skills. The productivity of each operator was considered as dynamic, developing or degrading depending on the prior allocation decisions. The solving approach mainly uses decision-based genetic algorithms, in which, chromosomes don’t represent directly the problem solution; they simply present three decisions: tasks’ priorities for execution, actors’ priorities for carrying out these tasks, and finally the priority of working time strategy that can be considered during the specified working period. Also the principle of critical skill was taken into account. Based on these decisions and during a serial scheduling generating scheme, one can in a sequential manner introduce the project scheduling and the corresponding workforce allocations

Multi crteria decision making and its applications : a literature review

This paper presents current techniques used in Multi Criteria Decision Making (MCDM) and their applications. Two basic approaches for MCDM, namely Artificial Intelligence MCDM (AIMCDM) and Classical MCDM (CMCDM) are discussed and investigated. Recent articles from international journals related to MCDM are collected and analyzed to find which approach is more common than the other in MCDM. Also, which area these techniques are applied to. Those articles are appearing in journals for the year 2008 only. This paper provides evidence that currently, both AIMCDM and CMCDM are equally common in MCDM

Planning and scheduling research at NASA Ames Research Center

Planning and scheduling is the area of artificial intelligence research that focuses on the determination of a series of operations to achieve some set of (possibly) interacting goals and the placement of those operations in a timeline that allows them to be accomplished given available resources. Work in this area at the NASA Ames Research Center ranging from basic research in constrain-based reasoning and machine learning, to the development of efficient scheduling tools, to the application of such tools to complex agency problems is described

Vision 2020: The Role and Scope of Operations Research Models

In this theme article, we summarize the broad characteristics of Vision 2020 (a document which outlines the transformation process related to evolution of India as a developed nation by 2020) as envisaged by Dr. A.P.J. Abdul Kalam. We discuss the enabling role of our discipline related to this critical national (social) transformation process. This theme article is organized in three segments. The first segment, which is drawn heavily based on the published work by Dr. A.P.J. Abdul Kalam introduces the salient features of Vision 2020 and a road map related to realizing this national dream. The second segment sketches the evolution of operations research as a scientific discipline in the international and Indian context. The third and final segment of the article relate OR tools and techniques that can facilitate the planning and implementation of several projects / activities / policies in the overall context of Vision 2020.

A variable neighborhood search simheuristic for project portfolio selection under uncertainty

With limited nancial resources, decision-makers in rms and governments face the task of selecting the best portfolio of projects to invest in. As the pool of project proposals increases and more realistic constraints are considered, the problem becomes NP-hard. Thus, metaheuristics have been employed for solving large instances of the project portfolio selection problem (PPSP). However, most of the existing works do not account for uncertainty. This paper contributes to close this gap by analyzing a stochastic version of the PPSP: the goal is to maximize the expected net present value of the inversion, while considering random cash ows and discount rates in future periods, as well as a rich set of constraints including the maximum risk allowed. To solve this stochastic PPSP, a simulation-optimization algorithm is introduced. Our approach integrates a variable neighborhood search metaheuristic with Monte Carlo simulation. A series of computational experiments contribute to validate our approach and illustrate how the solutions vary as the level of uncertainty increases

Robust competence assessment for job assignment

International audienceAllocating the right person to a task or job is a key issue for improving quality and performance of achievements, usually addressed using the concept of "competences". Nevertheless, providing an accurate assessment of the competences of an individual may be in practice a difficult task. We suggest in this paper to model the uncertainty on the competences possessed by a person using a possibility distribution, and the imprecision on the competences required for a task using a fuzzy constraint, taking into account the possible interactions between competences using a Choquet Integral. As a difference with comparable approaches, we then suggest to perform the allocation of persons to jobs using a Robust Optimisation approach, allowing to minimize the risk taken by the decision maker. We first apply this framework to the problem of selecting a candidate within n for a job, then extend the method to the problem of selecting c candidates for j jobs (c ≥ j) using the leximin criterion

The right place at the right time: assisting spatio-temporal planning in construction

21st - 24th October 2003 This paper describes research carried out for requirements capture in the development of a computer-based decision support tool (VIRCON) for space-time scheduling and visualisation of construction tasks. The focus was on pre-tender work and involved interviews with construction planners. Both space-time scheduling and visualisation of tasks are largely informal/intuitive processes for planners. They form an important part of the planner\'s risk identification function. Planners tend to opt for a robust spatio-temporal schedule rather than an optimal one. They require decision support tools that are quick and easy to use rather than highly sophisticated. The research highlights the extent to which construction planning is a communicative and co-operative activity in addition to a complex problem-solving one. Questions arise about the cost to the client of non-involvement by the construction planner at the design stage, the costs of short pre-tender periods, inadequate design data and sub-optimal construction periods specified in tender documents