A Memetic Algorithm for Concurrent Project Scheduling, Materials Ordering and Suppliers Selection Problem

In project planning, traditionally, the project managers first schedule the project activities, and then plan for materials ordering and supplier selection. This disintegrated approach lacks in planning co-ordination and causes a loss in expected profit for the organization. In this study, a concurrent model is proposed for resource constraint project scheduling with materials ordering and suppliers selection problems. The proposed model aims to maximize overall net present value for the organization considering ordering cost, procurement cost, materials holding cost, and the project's deadline penalty cost. The resource constraint project scheduling with materials ordering and suppliers selection is an NP-hard problem. Thus, a memetic algorithm hybridizing the genetic algorithm with a forward-backward improvement based local search is proposed to solve the proposed model. The proposed algorithm is tested on self-generated 120 instances varied from 30 to 60 activity projects with 4 to 8 suppliers. Experimental results show that the proposed genetic algorithm-based memetic algorithm approach generates better solutions than the standalone genetic algorithm. The concurrent project scheduling with materials ordering and supplier selection approach and solution methods have a significant implication for the managers to complete the project in an economic and timely manner. (C) 2021 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (https://crativecommons.org/licenses/by-nc-nd/4.0) Peer-review under responsibility of the scientific committee of KES International.