Resource preference based improvement heuristics for resource portfolio problem

The multi-project problem environment under consideration involves multiple-projects with activities having alternative execution modes, a general resource budget and a resource management policy that does not allow sharing of resources among projects. The multi-project scheduling model for this problem environment is called Resource Portfolio Problem. There are three basic conceptual problems in RPP: (i) determining the general resource capacities from the given general resource budget (general resource capacities determination); (ii) dedication of the general resource capacities to projects (resource dedication) and finally (iii) scheduling of individual projects with the given resource dedications. In this study, different preference based improvement heuristics are proposed for general resource capacities determination and resource dedication conceptual problems. For general resource capacities determination, the current general resource capacity values are changed according to the resource preferences such that the resulting capacity state would be more preferable. Similarly for resource dedication, resource dedication values of projects are changed according to the preferences of projects for resources such that the resulting resource dedication state would be more preferable. These two improvement heuristics separates and couples the conceptual problems. Different preference calculation methods are proposed employing Lagrangian relaxation and linear relaxation of MRCPSP formulation

Different resource management policies in multi-mode resource constrained multi-project scheduling

This study investigates different resource management policies in resource constrained multi-project problem environments. The problem environment under investigation has alternative modes for activities, a set of renewable and nonrenewable resources used by activities and further considerations such as general resource budget. The characterization of the way resources are used by individual projects in the multiproject environment is called resource management policy in this study. The solution approaches in the literature for multi-project problems generally defines the resources as a pool that can be shared by all the projects which in fact creates a general assumption for the resource usage characteristics. This resource management policy is referred as resource sharing policy in this study. Resource sharing policy can be invalid in some certain cases where sharing assumption is not feasible because of some characteristics of resources and/or projects which require different resource management policies for the multi-project environment. According to the characteristics of resources and projects, resource management policies such as resource dedication, relaxed resource dedication and generalized resource management policies can be defined. In this paper, these resource management policies will be defined and their mathematical formulations will be presented and discussed

Mathematical models for FMS loading and part type selection with flexible process plans

The loading problem in flexible manufacturing systems (FMS) consider several different manufacturing settings and objective functions but some crucial aspects of FMS environments, such as flexible process plans (FPP), have not yet received adequate attention. FPPs are vital in coping with bottlenecks and breakdowns, and decreasing the flow time. Modelling FPPs within a loading model, however, increases the problem complexity. In this study, we work on the integrated version of FMS part type selection and loading problems, and propose two models that consider operation allocation at different levels of detail for an FMS with FPP. Operation allocation is modelled explicitly along with tool loading in our first model, while the second one considers it implicitly to obtain a more compact and efficient formulation. Both models show remarkable reduction in run time compared to an existing loading model proposed for a similar FMS environment

Mathematical models for FMS loading and part type selection with flexible process plans

The loading problem in Flexible Manufacturing Systems (FMS) consider several different manufacturing settings and objective functions but some crucial aspects of FMS environments, such as flexible process plans (FPP), have not yet received adequate attention. FPPs are vital in coping with bottlenecks and breakdowns, and decreasing the flow time. Modeling FPPs within a loading model, however, increases the problem complexity. In this study, we work on the integrated version of FMS part type selection and loading problems, and propose two models that consider operation allocation at different levels of detail for an FMS with FPP. Operation allocation is modeled explicitly along with tool loading in our first model, while the second one considers it implicitly to obtain a more compact and efficient formulation. Both models show remarkable reduction in run time compared to an existing loading model proposed for a similar FMS environment