In this paper, the advantages and performance of genetic programming in use of error recovery planning in robotic assembly systems is discussed. Existing systems use polynomial time planning techniques or heuristics to produce error recovery plans. However, these systems require translation of the generated plans to working controller codes. An alternative approach could be the use of Genetic P...

Re-entrant scheduling is an important search problem with many constraints in the flow shop. In the literature, a number of approaches have been investigated from exact methods to meta-heuristics. This paper presents a genetic algorithm that encodes the problem as multi-level chromosomes to reflect the dependent relationship of the re-entrant possibility and resource consumption. The novel enco...

This paper considers a scheduling problem for parallel burn-in ovens in the semiconductor manufacturing industry. An oven is a batch processing machine with restricted capacity. The batch processing time is set by the longest processing time among those of all the jobs contained in the batch. All jobs are assumed to have the same due date. The objective is to minimize the sum of the absolute de...

Assembly line balancing (ALB) aims at distributing those work required to assemble a product in mass or series production among a set of workstations in an assembly line. Heuristics approaches, in corporation with computer simulation, have demonstrated a number of advantages in practice. Recognizing the importance of interactions between production planners and the scheduling system, this paper...

To deal with computationally hard problems, approximate algorithms are used to provide reasonably good solutions in practical time. Genetic algorithms are an example of the meta-heuristics which were recently introduced and which have been successfully applied to a variety of problems. We propose to use dynamic programming in the process of obtaining new generation solutions in the genetic algo...

In this paper, the problem of lot sizing, scheduling and delivery of several items in a twostage supply chain over a finite planning horizon is studied. Single supplier via a flexible flow line production system (FFL), produces several items and delivers them directly to an assembly facility. Based on basic period (BP) strategy, a new mixed zero-one nonlinear programming model has been develope...

Many military planning problems are difficult to solve using pure mathematical programming techniques. One such problem is scheduling unmanned aerial vehicles (UAVs) in military operations subject to dynamic movement and control constraints. This problem is instead formulated as a dynamic programming problem whose approximate solution is obtained via the Assignment Scheduling Capability for UAV...

We study the problem of (off-line) broadcast scheduling in minimizing total flow time and propose a dynamic programming approach to compute an optimal broadcast schedule. Suppose the broadcast server has k pages and the last page request arrives at time n. The optimal schedule can be computed in O(k3(n + k)k−1) time for the case that the server has a single broadcast channel. For m channels cas...

in this paper, we consider a flow shop scheduling problem with availability constraints (fsspac) for the objective of minimizing the makespan. in such a problem, machines are not continuously available for processing jobs due to preventive maintenance activities. we proposed a mixed-integer linear programming (milp) model for this problem which can generate non-permutation schedules. furthermor...

Genetic algorithms (GAs) are search heuristics used to solve global optimization problems in complex search spaces. We wish to show that the e6ciency of GAs in solving a &owshop problem can be improved signi7cantly by tailoring the various GA operators to suit the structure of the problem. The &owshop problem is one of scheduling jobs in an assembly line with the objective of minimizing the com...