Scheduling Limited Resources in Engineering Projects

Because of high customizations in the one-of-a-kind production companies (OKP companies), these companies need to find a way for reducing the production cost, shortening the production lead-time, and maintaining the quality of the productions as in the mass production system MP.s. Currently, production scheduling in OKP system follows the traditional mass production system, which focus on time and inventory, and it is inapplicable. Actually, OKP system works based on customer requirements, where each order can be representing as multi-project based. In this paper, One-of-a-kind production OKP has been referred as a project-based production and as a flexible resource- constrained project scheduling problems (FRCPSs); because in practice, some of project activities cannot be pre-determined due to its high customizations and great uncertainties. A new model has been proposed based on these assumptions to create production schedules for OKP system, which focuses on time and resources as in project management system PM. s, and deals with the problem which have three categories of project activities A, B, and C. The per-findings indicated that the model enhances the applicability of resulting schedules, emulates what a project manager in practice does (i.e. adding or removing resources from tasks to have the project completed in time), increase the number of feasible solutions, and reduces the project duration

Improved discrete cuckoo search for the resource-constrained project scheduling problem

YesAn Improved Discrete Cuckoo Search (IDCS) is proposed in this paper to solve resource-constrained project scheduling problems (RCPSPs). The original Cuckoo Search (CS) was inspired by the breeding behaviour of some cuckoo species and was designed specifically for application in continuous optimisation problems, in which the algorithm had been demonstrated to be effective. The proposed IDCS aims to improve the original CS for solving discrete scheduling problems by reinterpreting its key elements: solution representation scheme, Lévy flight and solution improvement operators. An event list solution representation scheme has been used to present projects and a novel event movement and an event recombination operator has been developed to ensure better quality of received results and improve the efficiency of the algorithm. Numerical results have demonstrated that the proposed IDCS can achieve a competitive level of performance compared to other state-of-the-art metaheuristics in solving a set of benchmark instances from a well-known PSPLIB library, especially in solving complex benchmark instances.Partially funded by the Innovate UK project HARNET – Harmonised Antennas, Radios and Networks under contract no. 100004607

Solving Resource Constrained Project Scheduling Problems (RCPSP) with Remanufacturing

Scheduling is one of the crucial issues in the project planning phase. Completing the project in the desired duration with the available resources with minimum cost is a big challenge for project managers. In the recent decades, several approaches have been proposed to deal with the resource constraints in scheduling. It can create a serious bottleneck and drastically change the flow of the activities. Moreover, resource constrains can change the project duration in crashing the project even if the activity (which creates the bottleneck) is not on the critical path. To address this issue, a new approach for Resource Constrained Project Scheduling (RCPS) is proposed when the remanufacturing option for some activities is available in order to crash the project. In this research, first a mathematical model for RCPS is presented. Then, a new algorithm is proposed to shorten the project duration by activating remanufacturing line (if possible) or paying the crash cost. The proposed algorithm is implemented in MATLAB and some computational experiments have been done to demonstrate the effectiveness and sensitivity of the proposed procedures. The algorithm is also validated on a practical case study which is a manufacturing industry in the northern Ontario

Balancing labor requirements in a manufacturing environment

“This research examines construction environments within manufacturing facilities, specifically semiconductor manufacturing facilities, and develops a new optimization method that is scalable for large construction projects with multiple execution modes and resource constraints. The model is developed to represent real-world conditions in which project activities do not have a fixed, prespecified duration but rather a total amount of work that is directly impacted by the level of resources assigned. To expand on the concept of resource driven project durations, this research aims to mimic manufacturing construction environments by allowing a non-continuous resource allocation to project tasks. This concept allows for resources to shift between projects in order to achieve the optimal result for the project manager. Our model generates a novel multi-objective resource constrained project scheduling problem. Specifically, two objectives are studied; the minimization of the total direct labor cost and the minimization of the resource leveling. This research will utilize multiple techniques to achieve resource leveling and discuss the advantage each one provides to the project team, as well as a comparison of the Pareto Fronts between the given resource leveling and cost minimization objective functions. Finally, a heuristic is developed utilizing partial linear relaxation to scale the optimization model for large scale projects. The computation results from multiple randomly generated case studies show that the new heuristic method is capable of generating high quality solutions at significantly less computational time”--Abstract, page iv

Desenvolvimento de uma ferramenta para gestão de capacidades em projetos de industrialização: estudo de caso na indústria automóvel

Dissertação de mestrado em Engenharia de SistemasOs projetos de industrialização são projetos considerados fundamentais para a introdução de novos produtos no mercado. Estes projetos representam uma das etapas de maior criação de valor em toda a indústria, o que pode também explicar o crescimento da literatura sobre o tema. Para gerir melhor estes projetos é crucial usar técnicas robustas para a gestão de projetos. Dentro dessas técnicas podemos incluir as técnicas que permitem fazer um melhor uso da capacidade para gerir projetos de industrialização, foco deste trabalho. Assim, o presente trabalho foi realizado como um estudo de caso, realizado na Bosch Car Multimedia, com o intuito de identificar que métodos e técnicas poderiam acrescer melhorias na gestão de capacidades em projetos de industrialização. Do vasto campo de conhecimento existente na gestão projetos, o presente trabalho concentra-se nas áreas de conhecimento de Project Resources Management e Project Schedule Management. O alinhamento destas duas áreas de conhecimento da gestão de projetos resultou numa ferramenta que auxilia na gestão do portfólio de projetos de industrialização, nomeadamente na atribuição dos gestores de projeto aos projetos, tendo em conta a sua capacidade e suas competências. Esta ferramenta utiliza um modelo matemático e uma mateurística para construir os cronogramas do projeto sem que ocorra uma sobre alocação dos gestores dos projetos. Pode verificar que a ferramenta constrói cronogramas num tempo médio de 35,56 segundos em cenários sem due dates e um tempo médio 168,70 segundos em cenários com due dates. Além disso reúne as informações dos projetos e gestores de projetos num dashboard, com o intuito de identificar o nível de aproveitamento da capacidade disponível para gerir o portfólio de projetos.Industrialization projects are projects that are considered crucial for the introduction of new products in the market. These projects represent one of the highest value-creation stages of the entire industry, which can also explain the growing literature on the subject. To better manage these projects it is crucial to use project management robust techniques. Within these techniques we can include techniques that allow to make a better use of the capacity to manage industrialization projects, the focus of this research. Thus, this work was carried out as a case study, conducted at Bosch Car Multimedia, in order to identify which methods and techniques could add improvements in capacity management in industrialization projects. From the vast field of knowledge in project management, this work focused on the Project Resource Management and Project Schedule Management knowledge areas. Aligning these two knowledge areas of project management, resulted in a tool that aims to help in managing the industrialization projects portfolio, in particular in the assignment of project managers to projects, taking into account their capacity and skills. This tool makes use of a mathematical model and a matheuristic to construct time schedules without over-allocation for the project managers. It can be observed that the tool builds time-schedules in an average time of 35.56 seconds in scenarios without due dates and an average time of 168.70 seconds in scenarios with due dates. Also, it gathers information from projects and project managers in a dashboard to identify the capacity utilization rate available to manage the project portfolio

Hybridization of enhanced ant colony system and Tabu search algorithm for packet routing in wireless sensor network

In Wireless Sensor Network (WSN), high transmission time occurs when search agent focuses on the same sensor nodes, while local optima problem happens when agent gets trapped in a blind alley during searching. Swarm intelligence algorithms have been applied in solving these problems including the Ant Colony System (ACS) which is one of the ant colony optimization variants. However, ACS suffers from local optima and stagnation problems in medium and large sized environments due to an ineffective exploration mechanism. This research proposes a hybridization of Enhanced ACS and Tabu Search (EACS(TS)) algorithm for packet routing in WSN. The EACS(TS) selects sensor nodes with high pheromone values which are calculated based on the residual energy and current pheromone value of each sensor node. Local optima is prevented by marking the node that has no potential neighbour node as a Tabu node and storing it in the Tabu list. Local pheromone update is performed to encourage exploration to other potential sensor nodes while global pheromone update is applied to encourage the exploitation of optimal sensor nodes. Experiments were performed in a simulated WSN environment supported by a Routing Modelling Application Simulation Environment (RMASE) framework to evaluate the performance of EACS(TS). A total of 6 datasets were deployed to evaluate the effectiveness of the proposed algorithm. Results showed that EACS(TS) outperformed in terms of success rate, packet loss, latency, and energy efficiency when compared with single swarm intelligence routing algorithms which are Energy-Efficient Ant-Based Routing (EEABR), BeeSensor and Termite-hill. Better performances were also achieved for success rate, throughput, and latency when compared to other hybrid routing algorithms such as Fish Swarm Ant Colony Optimization (FSACO), Cuckoo Search-based Clustering Algorithm (ICSCA), and BeeSensor-C. The outcome of this research contributes an optimized routing algorithm for WSN. This will lead to a better quality of service and minimum energy utilization