Tabu search algorithms for job-shop problems with a single transport robot

We consider a generalized job-shop problem where the jobs additionally have to be transported between the machines by a single transport robot. Besides transportation times for the jobs, empty moving times for the robot are taken into account. The objective is to determine a schedule with minimal makespan. \u

An optimization framework for solving capacitated multi-level lot-sizing problems with backlogging

This paper proposes two new mixed integer programming models for capacitated multi-level lot-sizing problems with backlogging, whose linear programming relaxations provide good lower bounds on the optimal solution value. We show that both of these strong formulations yield the same lower bounds. In addition to these theoretical results, we propose a new, effective optimization framework that achieves high quality solutions in reasonable computational time. Computational results show that the proposed optimization framework is superior to other well-known approaches on several important performance dimensions

A Combined Adaptive Tabu Search and Set Partitioning Approach for the Crew Scheduling Problem with an Air Tanker Crew Application

This research develops the first metaheuristic approach to the complete air crew scheduling problem. It develops the first dynamic, integrated, set-partitioning based vocabulary scheme for metaheuristic search. Since no benchmark flight schedules exist for the tanker crew scheduling problem, this research defines and develops a Java™ based flight schedule generator. The robustness of the tabu search algorithms is judged by testing them using designed experiments. An integer program is developed to calculate lower bounds for the tanker crew scheduling problem objectives and to measure the overall quality of solutions produced by the developed algorithms

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;

Scheduling flexible flowshops with sequence -dependent setup times

This dissertation addresses the scheduling problem in a flexible flowshop with sequence-dependent setup times. The production line consists of S production stages, each of which may have more than one non-identical (uniform) machines. Prior to processing a job on a machine at the first stage, a setup time from idling is needed. Also sequence dependent setup times (SDST) are considered on each machine in each stage. The objective of this research is to minimize the makespan. A mathematical model was developed for small size problems and two heuristic algorithms (Flexible Flowshop with Sequence Dependent Setup Times Heuristic (FFSDSTH) and Tabu Search Heuristic (TSH)) were developed to solve larger, more practical problems. The FFSDSTH algorithm was developed to obtain a good initial solution which can then be improved by the TSH algorithm. The TSH algorithm uses the well-known Tabu Search metaheuristic. In order to evaluate the performance of the heuristics, two lower bounds (Forward and Backward) were developed. The machine waiting time, idle time, and total setup and processing times on machines at the last stage were used to calculate the lower bound. Computational experiments were performed with the application of the heuristic algorithms and the lower bound methods. Two quantities were measured: (1) the performance of the heuristic algorithms obtained by comparing solutions with the lower bounds and (2) the relative improvement realized with the application of the TSH algorithm to the results obtained with the FFSDSTH algorithm. The performance of the heuristics was evaluated using two measures: solution quality and computational time. Results obtained show that the heuristic algorithms are quite efficient. The relative improvement yielded by the TSH algorithm was between 2.95 and 11.85 percent