We consider the multi-mode resource-constrained project scheduling problem (MRCPSP) with renewable resources. In MRCPSP, an activity can be executed in one of many possible modes; each mode having different resource requirements and accordingly different activity durations. We assume that all resources are renewable from period to period, such as labor and machines. A solution to this problem b...

The multimode resource-constrained project scheduling problem (MRCPSP) is an extension of the single-mode resourceconstrained project scheduling problem (RCPSP). In this problem, each project contains a number of activities which precedence relationship exist between them besides their amount of resource requirements to renewable and non-renewable resources are limited to the resources availabi...

In this paper, we introduce a new multimode project scheduling problem, taking into account finish-to-start precedence relations among project activities as well as renewable and nonrenewable resources constraints. We suppose renewable resources are hired and not accessible in all time intervals of a project. In other words, there is a presumed release date as well as a mandated due date for ea...

in this paper, a fully informed particle swarm (fips) algorithm is proposed for solving the multi-mode resource-constrained project scheduling problem (mrcpsp) with minimization of project makespan as the objective subject to resource and precedence constraints. in the proposed fips, a random key and the related mode list (ml) representation scheme are used as encoding schemes and the multi-mod...

The aim of a multi-mode resource-constrained project scheduling problem (MRCPSP) is to assign resource(s) with the restricted capacity to an execution mode of activities by considering relationship constraints, to achieve pre-determined objective(s). These goals vary with managers or decision makers of any organization who should determine suitable objective(s) considering organization strategi...

The integration of machine learning methods into meta-heuristic search techniques is currently an important topic in the field of combinatorial optimisation. It is often referred to as intelligent optimisation [1]. Learning has the potential of helping the search process in several ways. Searching for instance, can become more generic when online learning and automation mechanisms tune the crit...

in this paper, a new genetic algorithm (ga) is presented for solving the multi-mode resource-constrained project scheduling problem (mrcpsp) with minimization of project makespan as the objective subject to resource and precedence constraints. a random key and the related mode list (ml) representation scheme are used as encoding schemes and the multi-mode serial schedule generation scheme (mssg...