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.     

Using the generalized maximum covering location model to control a project’s progress

Project control consists of monitoring a project’s progress at so called control points, finding possible deviations from the baseline schedule and if necessary, making adjustments to the deviated schedule subject to the available control budget, the adjusting strategies and also other technical and environmental possibilities in order to bring the schedule back on the right track. In this study, we adapt for the first time the generalized maximum covering location model to determine the adjusting strategies such that the maximum control coverage is achieved, i.e. under the given constraints, a schedule that is globally as close to the baseline schedule as possible is obtained. Numerical examples are given to illustrate the intricacies of the proposed method and also to demonstrate its applicability.

     

Production planning in fuzzy environment

This paper describes a fuzzy system designed to support production planning in an industrial unit producing cardboard boxes. In this industrial unit, orders forn boxes of widthw, lengthl, heighth, made ofq layers of typek paper for delivery int units of time are produced. In the production of such orders apart from meeting the orders specifications, it is usually tried to minimize the margin trim loss, the number of machine setups and the holding cost of the finished orders. Considering the dynamism of production systems that are influenced by such factors as market demand fluctuations, changes in commercial priorities, raw material availability and production capabilities, we solve this multi-objective problem by fuzzy set theory.     

Tri-directional Scheduling Scheme: Theory and Computation

In this paper we introduce a new scheduling scheme based on so called tri-directional scheduling strategy to solve the well known resource constrained project scheduling problem. In order to demonstrate the effectiveness of tri-directional scheduling scheme, it is incorporated into a priority rule based parallel scheduling scheme. Theoretical and numerical investigations show that the tri-directional scheduling scheme outperforms forward, backward and even bidirectional schemes depending on the problem structure and the priority rule used. Based on empirical evidence, it seems that as the number of activities are increased, the tri-directional scheduling scheme performs better irrespective of the priority rule used. This suggests that tri-directional scheme should also be applied within the category of heuristic methods.