Ümit Bilge

A genetic algorithm approach to the simultaneous scheduling of machines and automated guided vehicles

Abstract This article addresses the problem of simultaneous scheduling of machines and a number of identical automated guided vehicles (AGVs) in a flexible manufacturing system (FMS) so as t minimize the makespan. For solving this problem, a genetic algorithm (GA) is proposed. Here, chromosomes represent both operation sequencing and AGV assignment dimensions of the search space. A third dimension, time, is implicitly given by the ordering of operations of the chromosomes. A special uniform crossover operator is developed which produces one offspring from two parent chromosomes. It transfers any patterns of operation sequences and/or AGV assignments that are present in both parents to the child. Two mutation operators are introduced; a bitwise mutation for AGV assignments and a swap mutation for operations. Any precedence infeasibility resulting from the operation swap mutation is removed by a repair function. The schedule associated with a given chromosome is determined by a simple schedule builder. After a number of problems are solved to evaluate various search strategies and to tune the parameters of the proposed GA, 180 test problems are solved to evaluate various search lower bound is introduced and compared with the results of GA. In 60% of the problems GA reaches the lower bound indicating optimality. The average deviation from the lower bound over all problems is found to be 2.53%. Additional comparison is made with the time window approach suggested for this same problem using 82 test problems from the literature. In 59% of the problems GA outperforms the time window approach where the reverse is true only in 6% of the problems.

A Time Window Approach to Simultaneous Scheduling of Machines and Material Handling System in an FMS

This paper exploits the interactions between the machine scheduling and the scheduling of the material handling system in an FMS by addressing them simultaneously. The material transfer between machines is done by a number of identical automated guided vehicles (AGVs) which are not allowed to return to the load/unload station after each delivery. This operating policy introduces an additional complexity to the problem because it results in sequence-dependent travel times for the deadheading trips between successive loaded trips of the AGVs. The problem is formulated as a nonlinear mixed integer programming model. Its objective is makespan minimization. The formulation consists of constraint sets of a machine scheduling subproblem and a vehicle scheduling subproblem which interact through a set of time window constraints for the material handling trip starting times. An iterative procedure is developed where, at each iteration, a new machine schedule is generated by a heuristic procedure, the operation completion times obtained from this schedule are used to construct time windows for the trips, and a feasible solution is searched for the second subproblem, which is handled as a sliding time window problem. The procedure is numerically tested on 90 example problems.

A tabu search algorithm for parallel machine total tardiness problem

In this study, we consider the problem of scheduling a set of independent jobs with sequence dependent setups on a set of uniform parallel machines such that total tardiness is minimized. Jobs have nonidentical due dates and arrival times. A tabu search (TS) approach is employed to attack this complex problem. In order to obtain a robust search mechanism, several key components of TS such as candidate list strategies, tabu classifications, tabu tenure and intensification/diversification strategies are investigated. Alternative approaches to each of these issues are developed and extensively tested on a set of problems obtained from the literature. The results obtained are considerably better than those reported previously and constitute the best solutions known for the benchmark problems as to date.

A tabu search algorithm for the single machine total weighted tardiness problem

In this study, a tabu search (TS) approach to the single machine total weighted tardiness problem (SMTWT) is presented. The problem consists of a set of independent jobs with distinct processing times, weights and due dates to be scheduled on a single machine to minimize total weighted tardiness. The theoretical foundation of single machine scheduling with due date related objectives reveal that the problem is NP-hard, rendering it a challenging area for meta-heuristic approaches. This paper presents a totally deterministic TS algorithm with a hybrid neighborhood and dynamic tenure structure, and investigates the strength of several candidate list strategies based on problem specific characteristics in increasing the efficiency of the search. The proposed TS approach yields very high quality results for a set of benchmark problems obtained from the literature. � 2005 Elsevier B.V. All rights reserved.

AGV systems with multi-load carriers: Basic issues and potential benefits

Abstract An alternative to increasing automated guided vehicle (AGV) fleet size to improve vehicle availability for material transport requests is to introduce vehicles with multiple load-carrying capacities. Aside from alleviating communication and congestion problems, the use of multiple-load carriers can potentially reduce the deadhead or unproductive time of vehicles. This paper discusses several key issues related to multiple-load AGV systems and demonstrates the potential benefits of using them. Alternative vehicle dispatching strategies for multiple-load AGVs are discussed, stressing that different considerations are involved in dispatching empty and partially loaded vehicles. The effectiveness of single-load and two-load AGV systems is compared using simulation. The results show that, with multiple-load vehicles, the sensitivity of AGV system performance to guidepath layout is decreased, and the job input rate, which the AGV system can effectively handle without becoming a bottleneck for the overall system, is significantly increased. The relative effectiveness of selected control strategies is also investigated.

Simultaneous scheduling of machines and automated guided vehicles

Abstract This paper is an attempt to make scheduling of AGVs an integral part of the overall scheduling activity in an FMS environment. The sequence-dependent nature of travel times for the deadheading trips between successive loaded trips of the AGVs increases the problem difficulty. The problem is decomposed into two subproblems, and previous work on machine scheduling and vehicle scheduling has been exploited to arrive at an iterative heuristic procedure where makespan is the performance criterion. At each iteration, a new machine schedule, generated by a heuristic procedure, is investigated for its feasibility to the vehicle scheduling subproblem. The operation completion times obtained from the machine schedule are used to construct time windows for each material handling trip, and the second subproblem is handled as a sliding time window problem. A set of problems are solved to analyse the impact of the process times/travel times ratio on the performance of the procedure. The interaction between the...

Multi-mode resource constrained multi-project scheduling and resource portfolio problem

This paper introduces a multi-project problem environment which involves multiple projects with assigned due dates; activities that have alternative resource usage modes; a resource dedication policy that does not allow sharing of resources among projects throughout the planning horizon; and a total budget. Three issues arise when investigating this multi-project environment. First, the total budget should be distributed among different resource types to determine the general resource capacities, which correspond to the total amount for each renewable resource to be dedicated to the projects. With the general resource capacities at hand, the next issue is to determine the amounts of resources to be dedicated to the individual projects. The dedication of resources reduces the scheduling of the projects’ activities to a multi-mode resource constrained project scheduling problem (MRCPSP) for each individual project. Finally, the last issue is the efficient solution of the resulting MRCPSPs. In this paper, this multi-project environment is modeled in an integrated fashion and designated as the resource portfolio problem. A two-phase and a monolithic genetic algorithm are proposed as two solution approaches, each of which employs a new improvement move designated as the combinatorial auction for resource portfolio and the combinatorial auction for resource dedication. A computational study using test problems demonstrated the effectiveness of the solution approach proposed.

A hierarchical approach to FMS planning and control with simulation-based capacity anticipation

In this study, a hierarchical production planning and control system (HPPCS-FMS) framework for a Flexible Manufacturing System (FMS) is developed. The HPPCS-FMS is a three-level hierarchy embedded in a closed-loop structure where the main feedback is the anticipated effective capacity. The HPPCS-FMS exploits the flexibility inherent in the manufacturing system to respond effectively to a frequently changing demand mix. All levels benefit from flexible process plans as a means to use capacity effectively. Flexible process plans offer not only alternative machines for operations but also alternative sequences of operations for producing the same work piece. To implement the framework, the problems at each level are identified and modelled; the integration among the levels is defined and a simulation-based capacity anticipation mechanism is developed. The proposed HPPCS-FMS is tested under different scenarios. The results demonstrate that capacity anticipation considerably improves the performance.

Operational aircraft maintenance routing problem with remaining time consideration

The aircraft maintenance routing problem is one of the most studied problems in the airline industry. Most of the studies focus on finding a unique rotation that will be repeated by each aircraft in the fleet with a certain lag. In practice, using a single rotation for the entire fleet is not applicable due to stochasticity and operational considerations in the airline industry. In this study, our aim is to develop a fast responsive methodology which provides maintenance feasible routes for each aircraft in the fleet over a weekly planning horizon with the objective of maximizing utilization of the total remaining flying time of fleet. For this purpose, we formulate an integer linear programming (ILP) model by modifying the connection network representation. The proposed model is solved by using branch-and-bound under different priority settings for variables to branch on. A heuristic method based on compressed annealing is applied to the same problem and a comparison of exact and heuristic methods are provided. The model and the heuristic method are extended to incorporate maintenance capacity constraints. Additionally, a rolling horizon based procedure is proposed to update the existing routes when some of the maintenance decisions are already fixed.

Material handling considerations in the FMS loading problem with full routing flexibility

This study exploits machining and routing flexibility to effectively deal with the material handling requirements resulting from a frequently changing demand mix in a manufacturing system where material handling is a bottleneck. For this purpose, the objective function of the operation and tool loading problem is selected as the minimisation of the total distance traveled by parts during their production. Versatile machines and the flexible process plans offer full routing flexibility that enable the same workpiece to be processed using alternative sequences of operations on alternative machines. Three mathematical programming (MP) models and a genetic algorithm (GA) are proposed to solve this problem. The proposed MP formulations include a mixed-integer nonlinear programming (MINLP) model and two mixed-integer programming (MIP) models, which offer different representations for the flexible process plans. The GA is integrated with linear programming for fitness evaluation and incorporates several adaptive strategies for diversification. The performances of these solution methods are tested through extensive numerical experiments. The MP models are evaluated on the basis of the exact solutions they yield as well as how they lend themselves for GA fitness evaluation. The GA–LP integration works successfully for this hard-to-solve problem.