101 research outputs found
Broadcast scheduling for mobile advertising
We describe a broadcast scheduling system developed for a precision marketing firm specialized in location-sensitive permission-based mobile advertising using SMS (Short Message Service) text messaging. Text messages containing advertisements were sent to registered customers when they were shopping in one of two shopping centers in the vicinity of London. The ads typically contained a limited-time promotional offer. The company's problem was deciding which ads to send out to which customers at what particular time, given a limited capacity of broadcast time slots, while maximizing customer response and revenues from retailers paying for each ad broadcast. We solved the problem using integer programming with an interface in Microsoft Excel. The system significantly reduced the time required to schedule the broadcasts, and resulted both in increased customer response and revenues
Computational experience with a branch-and-bound procedure for the resource-constrained project scheduling problem with generalized precedence relations.
In a previous paper (De Reyck and Herroelen, 1996a), we presented an optimal procedure for the resource-constrained project scheduling problem (RCPSP) with generalised precedence relations (further denoted as RCPSP-GPR) with the objective of minimizing the project makespan. The RCPSP-GPR extends the RCPSP to arbitrary minimal and maximal time lags between the starting and completion times of activities. The procedure is a depth-first branch -and-bound algorithm in which the nodes in the search tree represent the original project network extended with extra precedence relations, which resolve a resource conflict present in the project network of the parent node. Resource conflicts are resolved using the concept of minimal delaying alternatives, i.e. minimal sets of activities which, when delayed, release enough resources to resolve the conflict. Precedence- and resource-based lower bounds as well as dominance rules are used to fathom large portions of the search tree. In this paper we report new computational experience with the algorithm using a new RCPSP-GPR random problem generator developed by Schwindt (1995). A comparison with other computational results reported in the literature is included.Scheduling;
An optimal procedure for the unconstrained max-NPV project scheduling problem with generalized precedence relations.
The unconstrained max-npv project scheduling problem involves the scheduling of the activities of a project in order to maximize its net present value. Assume a project represented in activity-on-mode (AoN) notation, in which the activities have a known duration and are subject to technological precedence constraints. Throughout each activity, a series of cash outflows and receipts may occur, which allows for the computation of a terminal cash flow value (positive or negative) upon the completion. The project is to be scheduled against a fixed deadline in the absence of resource constraints. Several procedures have been presented in the literature to cope with this problem. In this paper, we describe how one of the most efficient optimal procedures can be adapted to cope with generalized precedence relations, which introduce arbitrary minimal and maximal time lags between the start and completion of activities. The procedure has been programmed in Microsoft° Visual ++ 2.0 under Windows NT for use on a personal computer. Extensive computational results are reported.Scheduling; Optimal;
Local search methods for the discrete time/resource trade-off problem in project networks.
Abstract: In this paper we consider the discrete time/resource trade-off problem in project networks. Given a project network consisting of nodes (activities) and arcs (technological precedence relations specifying that an activity can only start when al of its predecessors have been completed), in which the duration of the activities is a discrete, on-increasing function of the amount of a single renewable resource committed to it, the discrete time/resource trade-off problem minimizes the project makespan subject to precedence constraints and a single renewable resource constraint. For each activity a work content is specified such that all execution modes (duration-resource pairs) for performing the activity are allowed as long as the product of the duration and the resource requirement is at least as large as the specified work content. We present a tabu search procedure which is based on subdividing the problem into a mode assignment phase and a resource-constrained project scheduling phase with fixed mode assignments. Extensive computational experience, including a comparison with other local search methods, is reported.Scheduling; Methods; Networks; Product; Assignment;
Phase transitions in project scheduling.
The analysis of the complexity of combinatorial optimization problems has led to the distinction between problems which are solvable in a polynomially bounded amount of time (classified in P) and problems which are not (classified in NP). This implies that the problems in NP are hard to solve whereas the problems in P are not. However, this analysis is based on worst-case scenarios. The fact that a decision problem is shown to be NP-complete or the fact that an optimization problem is shown to be NP-hard implies that, in the worst case, solving it is very hard. Recent computational results obtained with a well known NP-hard problem, namely the resource-constrained project scheduling problem, indicate that many instances are actually easy to solve. These results are in line with those recently obtained by researchers in the area of artificial intelligence, which show that many NP-complete problemsexhibit so-called phase transitions, resulting in a sudden and dramatic change of computational complexity based on one or more order parameters that are characteristic of the system as a whole. In this paper we provide evidence for the existence of phase transitions in various resource-constrained project scheduling problems. We discuss the use of network complexity measures and resource parameters as potential order parameters. We show that while the network complexity measures seem to reveal continuous easy-hard or hard-easy phase-transitions, the resource parameters exhibit an easy-hard-easy transition behaviour.Networks; Problems; Scheduling; Algorithms;
A branch-and-bound procedure for the resource-constrained project scheduling problem with generalized precedence relations.
We present an optimal procedure for the resource-constrained project scheduling problem (RCPSP) with generalized precedence relations (further denoted as RCPSP-GPR) with the objective of minimizing the project makespan. The RCPSP-GPR extends the RCPSP to arbitrary minimal and maximal time lags between the starting and completion times of activities. The procedure is a depth-first branch-and-bound algorithm in which the nodes in the search tree represent the original project network extended with extra precedence relations which resolve a resource conflict present in the parent node. Resource conflicts are resolved using the concept of minimal delaying alternatives, i.e. minimal sets of activities which, when delayed, release enough resources to resolve the conflict. Precedence and resource-based lower bounds as well as dominance rules are used to fathom large portions of the search tree. The procedure can be extended to other regular measures of performance by some minor modifications. Even non-regular measures of performance, such as the maximinization of the net present value of the project or resource levelling objectives, can be handled. The procedure has been programmed in Microsoft* Visual C++ for use on a personal computer. Extensive computational experience is obtained.Scheduling;
An optimal procedure for the resource-constrained project scheduling problem with discounted cash flows and generalized precedence relations.
In this paper, we study the resource-constrained project scheduling problem (RCPSP) with discounted cash flows and generalized precedence relations (further denoted as RCPSPDC-GPR). The RCPSPDC-GPR extends the RCPSP to (a) arbitrary minimal and maximal time lags between the starting and completion times of activities and (b) the non-regular objective function of maximizing the net present value of the project with positive and/or negative cash flows associated with the activities.). To the best of our knowledge, the literature on the RCPSPDC-GPR is completely void. We present a depth-first branch-and-bound algorithm in which the nodes in the search tree represent the original project network extended with extra precedence relations which resolve a number of resource conflicts. These conflicts are resolved using the concept of a minimal delaying mode (De Reyck and Herroelen, 1996b). An upper bound on the project net present value as well as several dominance rules are used to fathom large portions of the search tree. Extensive computational experience on a randomly generated benchmark problem set is obtained.Scheduling; Optimal; Discounted cash flow; Cash flow;
Algorithms for scheduling projects with generalized precedence relations.
Project scheduling under the assumption of renewable resource constraints and generalized precedence relations, i.e. arbitrary minimal and maximal time lags between the starting and completion times of the activities of the project, constitutes an important and challenging problem. Over the past few years considerable progress has been made in the use of exact solution procedure for this problem type and its variants. We review the fundamental logic and report new computational experience with a branch-and-bound procedure for optimally solving resource-constrained project scheduling problems with generalized precedence relations of the precedence diagramming type, i.e. start-start, start-finish, finish-start and finish-finish relations with minimal time lags for minimizing the project makespan. Subsequently, we review and report new results for several branch-and -bound procedures for the case of generalized precedence relations, including both minimal and maximal time lags, and demonstrate how the solution methodology can be expected to cope with other regular and nonregular objective functions such a smaximizing the net present value of a project.Networks; Problems; Scheduling; Algorithms; Functions; Net present value;
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