###### Abstract
These restrictions generally result in either the absence of any acceptable solutions or solutions that are not robust toward disruptions related to access to the resources used (e.g., related to cases of employee absenteeism). Of course, there are also further generalizations of the above-presented problem, e.g., extending it to the problem of dynamically scheduling jobs related to the introduction (or exchange) of new resources (e.g., hiring additional employees) or accepting (started in parallel with those still being implemented) new orders. It seems that an appropriate framework enabling the analytic implementation of that Dynamic Multi-skill Resource-constrained Multi-project Scheduling Problem (DMRPSP), as well as the processes occurring in it of a various nature and character (e.g., learning and forgetting curves and uncertain values of decision variables), will ensure only the adoption of the declarative modeling paradigm. This is because, in the considered class of broadly understood discrete event systems, declarative models allow the representation of nonlinear decision problems (described by logical formulas, algebraic operations, inequalities, etc.) as well as the formulation of decision-making versions of both the problem of analysis (seeking an answer to the question of whether there is a solution that meets the given expectations) and synthesis (seeking an answer to the question under which assumptions there is a solution that meets the given expectations). The presented advantages, combined with the possibility of building models with an open structure implemented in the constraint programming (CP) environment [19], make this representation an attractive alternative to building dedicated DSS class systems. In the above context, this study refers to our previous work on the assessment of a competence structure's robustness to employee absenteeism and job rotation planning, guaranteeing the maintenance of employees' competences at a given constant level [10; 20]. Inturn, this contribution is an attempt to use the previously gained experience for situations in which environmental dynamics play a major role. Examples of this type occur in cases of the dynamic assignment of newly hired employees, or planning new orders while re-scheduling previously established job rotation schedules. Our contribution in this regard includes:  
* The DMRPSP declarative reference model integrating DSPS and PCMP problems enabling both the analysis (searching for an answer to the question of whether a required solution is reachable) and synthesis (searching for an answer to the question of which changes to parameters guarantees a required solution). * Procedures of dynamic software project scheduling aimed at proactive planning with constrained multi-skilled resources, taking into account the influence of learning and forgetting effects. * The results of many computer experiments illustrating the possibilities of using the presented approach for the rapid prototyping of acceptable job rotation schedules, as well as its scalability. In summary, the novelty of the proposed approach results from two benefits of adopting the DMRPSP reference model. The first of these results is from its open structure that allows for the further specification and expansion of the model used. The second one boils down to the possibility of formulating and solving synthesis problems related to the search for changes in assumptions (e.g., fields of decision variables), guaranteeing the existence of the expected solution. The proposed DMRPSP reference model can be implemented in any declarative programming environment (Gurobi, IBM ILOG, Lingo, etc.). The solver built in this way can complement the existing DSS system with project manager support to answer the following questions:  
1. What change in the level of employee competences will result in the acceptance of additional orders to the already adopted plan of the project portfolio implementation? 2.