Approximation algorithms for dynamic resource allocation

We consider a problem of allocating limited quantities of M types of resources among N independent activities that evolve over T epochs. In each epoch, we assign to each activity a task which consumes resources, generates utility, and determines the subsequent state of the activity. We study the complexity of, and approximation algorithms for, maximizing average utility.     

A solution procedure for the discrete time, cost and quality tradeoff problem using electromagnetic scatter search

Decisions concerning a project’s expedition, traditionally involved considerations regarding time and cost tradeoff. It was recently suggested that the quality of a project should also be taken into considerations. In this paper, we propose a meta-heuristic solution procedure for the discrete time, cost and quality tradeoff problem. This problem involves the scheduling of project activities in order to minimize the total cost of the project while maximizing the quality of the project and also meeting a given deadline. We apply a so called electromagnetic scatter search to solve this problem. In this process, we initially generate a population of feasible solutions. In so doing, we use frequency memory to well sample the feasible region. A number of these solutions are then selected and improved locally. The improved solutions are then combined to generate new set of solutions. The combination process utilizes attraction–repulsion mechanisms borrowed from the electromagnetism theory. The whole process is stopped when no significant improvement in the set of solutions are observed. The validity of the proposed solution procedure is demonstrated, and its applicability is tested on a randomly generated large and complex problem having 19,900 activities.     

Uncertainty and stepwise investment

We analyze the optimal investment strategy of a firm that can complete a project either in one stage at a single freely chosen time point or in incremental steps at distinct time points. The presence of economies of scale gives rise to the following trade-off: lumpy investment has a lower total cost, but stepwise investment gives more flexibility by letting the firm choose the timing individually for each stage. Our main question is how uncertainty in market development affects this trade-off. The answer is unambiguous and in contrast with a conventional real-options intuition: higher uncertainty makes the single-stage investment more attractive relative to the more flexible stepwise investment strategy.     

The generation of stable project plans

This text summarises the PhD thesis that Roel Leus presented to obtain the degree of Doctor in Applied Economics at the Katholieke Universiteit Leuven, in September 2003. The promotor of the thesis was professor Willy Herroelen. The thesis is written in English and is available from the authors website. The goal of the thesis was to provide recommendations for the detailed scheduling of multi-project organisations, when a certain degree of uncertainty exists about a number of characteristics of the project. Up till now, the majority of the literature on project scheduling has consisted of deterministic models for planning a single project: both the uncertainty aspect as well as the intrinsic difficulty of coordination of a portfolio of projects have been largely ignored.Received: October 2003, MSC classification: 09B35, 90B36     

A Conversation with Lee Alvin DuBridge - Part II

Physicist Lee A. DuBridge became president of the California Institute of Technology in 1946. In this interview he recalls his dealings at Caltech with Linus Pauling; his memories of George W. Beadle, Theodore von Kármán, and J. Robert Oppenheimer; the military Vista Project at Caltech; and the difficulties surrounding the deportation of Hsue-Shen Tsien, Caltech's Goddard Professor of Jet Propulsion.     

Competence-driven project portfolio selection,scheduling and staff assignment

This paper presents a new model for project portfolio selection, paying specific attention to competence development. The model seeks to maximize a weighted average of economic gains from projects and strategic gains from the increment of desirable competencies. As a sub-problem, scheduling and staff assignment for a candidate set of selected projects must also be optimized. We provide a nonlinear mixed-integer program formulation for the overall problem, and then propose heuristic solution techniques composed of (1) a greedy heuristic for the scheduling and staff assignment part, and (2) two (alternative) metaheuristics for the project selection part. The paper outlines experimental results on a real-world application provided by the E-Commerce Competence Center Austria and, for a slightly simplified instance, presents comparisons with the exact solution computed by CPLEX.     

Proactive heuristic procedures for robust project scheduling: An experimental analysis

Solution-robust project scheduling is a growing research field aiming at constructing proactive schedules to cope with multiple disruptions during project execution. When stochastic activity durations are considered, including time buffers between activities is a proven method to improve the stability of a baseline schedule.     

Multi-objective decision analysis for competence-oriented project portfolio selection

This paper develops a multi-objective optimization model for project portfolio selection taking employee competencies and their evolution into account. The objectives can include economic gains as well as gains expressed in terms of aggregated competence increments according to pre-defined profiles. In order to determine Pareto-optimal solutions, the overall problem is decomposed into a master problem addressing the portfolio selection itself, and a slave problem dealing with a suitable assignment of personnel to the work packages of the selected projects over time. We provide an asymptotic approximation of the problem by a linearized formulation, which allows an efficient and exact solution of the slave problem. For the solution of the master problem, we compare the multi-objective metaheuristics NSGA-II and P-ACO. Experimental results both for synthetically generated test instances and for real-world test instances, based on an application case from the E-Commerce Competence Center Austria, are presented.     

A rule for slack allocation proportional to the duration in a PERT network

In this paper, we define a new rule for the resolution of the slack allocation problem in a PERT network. This problem exists of allocating existing extra time in some paths among the activities belonging to those paths. The allocation rule that we propose assigns extra time to the activities proportionally to their durations in such a way that no path duration exceeds the completion time of the whole project. This time allocation enables us to make a schedule for the PERT project under study. We give two characterizations of the rule and we compare it with others that have been previously defined in the literature.     

Skilled workforce scheduling in Service Centres

The Skilled Workforce Project Scheduling Problem (SWPSP) is a complex problem of task scheduling and resource assignment that comes up in the daily management of many company Service Centres (SC). The SWPSP considers many real characteristics faced daily by the SC: client-company service quality agreements that establish maximum dates for the beginning and the end of tasks with penalties for delays, criticality levels indicating the client-priority in processing each task, generalized precedence relationships that can produce cycle structures, time period and percentage time lags and variable task durations depending on the worker executing the task. Furthermore, the SC workforce is made up of specialist workers characterised by efficiency levels showing their efficiency and speed executing the several types of tasks. Each worker has his or her own timetable.