A Hybrid CLP/MP Approach to Modeling and Solving Resource-Constrained Scheduling Problems with Logic Constraints

Constrained scheduling problems are common in everyday life and especially in: distribution, manufacturing, project management, logistics, supply chain management, software engineering, computer networks etc. A large number of integer and binary decision variables representing the allocation of different constrained resources to activities/jobs and constraints on these decision variables are typical elements of the resource-constrained scheduling problems (RCSPs) modeling. Therefore, the models of RCSPs are more demanding, particularly when methods of operations research (OR) are used. By contrast, most resource-constrained scheduling problems can be easily modeled as instances of the constraint satisfaction problems (CSPs) and solved using constraint logic programming (CLP) or others methods. Moreover, CLP-based environments enable easy modeling of various types of constraints including logic constraints. In the CLP-based environment the problem definition is separated from the algorithms and methods used to solve the problem. Therefore, a hybrid approach to resource-constrained scheduling problems that combines an OR-based approach for problem solving and a CLP-based approach for problem modeling is proposed. To evaluate the efficiency and flexibility of this approach, illustrative examples of resource-constrained scheduling problems with logic constraints are implemented using hybrid CLP/MP approach.