Paz Perez-Gonzalez

Scheduling permutation flowshops with initial availability constraint: Analysis of solutions and constructive heuristics

In this paper, we address the problem of scheduling a set of jobs in a flowshop with makespan objective. In contrast to the usual assumption of machine availability presented in most research, we consider that machines may not be available at the beginning of the planning period, due to processing of previously scheduled jobs. We first formulate the problem, analyse the structure of solutions depending on a number of factors (such as machines, jobs, structure of the processing times, availability vectors, etc.), and compare it with its classical counterpart. Results indicate that the problem under consideration presents a different structure of solutions, and that it is easier than the classical permutation flowshop problem. In view of these results, we propose and test a number of fast heuristics for the problem.

Setting a common due date in a constrained flowshop: A variable neighbourhood search approach

In this paper we study a due date setting problem in a flowshop layout. The problem consists of scheduling a set of jobs arriving to the system together with jobs already present (denoted as old jobs), in order to set a common due date for the new jobs. Since the old jobs have a common due date that must not be violated, our problem is a rescheduling problem with the objective of minimising the makespan of the new jobs (thus obtaining the tightest possible due date for the new jobs) and a constraint since the maximum tardiness of the old jobs must be equal to zero. This approach leads to an interesting scheduling problem in which two different objectives are considered, each one for a subset of the jobs that must be scheduled. To the best of our knowledge, this type of problems have been scarcely considered in the literature, and only for very specific purposes. Since our problem is clearly NP-hard, a new heuristic based on variable neighbourhood search (VNS) has been designed. The computational results show that our proposed heuristic outperforms two existing heuristic methods for similar problems in the literature.

New approximate algorithms for the customer order scheduling problem with total completion time objective

In this paper, we study a customer order scheduling problem where a number of orders, composed of several product types, have to be scheduled on a set of parallel machines, each one capable to process a single product type. The objective is to minimise the sum of the completion times of the orders, which is related to the lead time perceived by the customer, and also to the minimisation of the work-in-process. This problem has been previously studied in the literature, and it is known to be NP-hard even for two product types. As a consequence, the interest lies on devising approximate procedures to obtain fast, good performing schedules. Among the different heuristics proposed for the problem, the ECT (Earliest Completion Time) heuristic by Leung et al. 6 has turned to be the most efficient constructive heuristic, yielding excellent results in a wide variety of settings. These authors also propose a tabu search procedure that constitutes the state-of-the-art metaheuristic for the problem. We propose a new constructive heuristic based on a look-ahead mechanism. The computational experience conducted shows that it clearly outperforms ECT, while having both heuristics the same computational complexity. Furthermore, we propose a greedy search algorithm using a specific neighbourhood that outperforms the existing tabu search procedure for different stopping criteria, both in terms of quality of solutions and of required CPU effort. HighlightsWe propose a new constructive heuristic for the customer order scheduling problem.We propose a greedy search algorithm for the customer order scheduling problem.We compare the proposals with existing approximate algorithms.We suggest that our proposals are the best-so-far heuristics for the problem.

Order Scheduling with Tardiness Objective: Improved Approximate Solutions

Abstract The problem addressed in this paper belongs to the topic of order scheduling, in which customer orders – composed of different individual jobs – are scheduled so the objective sought refers to the completion times of the complete orders. Despite the practical and theoretical relevance of this problem, the literature on order scheduling is not very abundant as compared to job scheduling. However, there are several contributions with the objectives of minimising the weighted sum of completion times of the orders, the number of late orders, or the total tardiness of the orders. In this paper, we focus in the last objective, which is known to be NP-hard and for which some constructive heuristics have been proposed. We intend to improve this state-of-the-art regarding approximate solutions by proposing two different methods: Whenever extremely fast (negligible time) solutions are required, we propose a new constructive heuristic that incorporates a look-ahead mechanism to estimate the objective function at the time that the solution is being built. For the scenarios where longer decision intervals are allowed, we propose a novel matheuristic strategy to provide extremely good solutions. The extensive computational experience carried out shows that the two proposals are the most efficient for the indicated scenarios.

Assessing scheduling policies in a permutation flowshop with common due dates

This paper focuses onto a situation arising in most real-life manufacturing environments when scheduling has to be performed periodically. In such a scenario, different scheduling policies can be adopted, being perhaps the most common to assume that, once a set of jobs has been scheduled, their schedule cannot be modified (‘frozen’ schedule). This implies that, when the next set of jobs is to be scheduled, the resources may not be fully available. Another option is assuming that the schedule of the previously scheduled jobs can be modified as long as it does not violate their due date, which has been already possibly committed to the customer. This policy leads to a so-called multi-agent scheduling problem. The goal of this paper is to discern when each policy is more suitable for the case of a permutation flowshop with common due dates. To do so, we carry out an extensive computational study in a test bed specifically designed to control the main factors affecting the policies, so we analyse the solution space of the underlying scheduling problems. The results indicate that, when the due date of the committed jobs is tight, the multi-agent approach does not pay off in view of the difficulty of finding feasible solutions. Moreover, in such cases, the policy of ‘freezing’ the schedule of the jobs leads to a very simple scheduling problem with many good/acceptable solutions. In contrast, when the due date has a medium/high slack, the multi-agent approach is substantially better. Nevertheless, in this latter case, in order to perceive the full advantage of this policy, powerful solution procedures have to be designed, as the structure of the solution space of the latter problem makes extremely hard to find optimal/good solutions.

The 2-stage assembly flowshop scheduling problem with total completion time: Efficient constructive heuristic and metaheuristic

Abstract In this paper, we address the 2-stage assembly scheduling problem where there are m machines in the first stage to manufacture the components of a product and one assembly station (machine) in the second stage. The objective considered is the minimisation of the total completion time. Since the NP-hard nature of this problem is well-established, most previous research has focused on finding approximate solutions in reasonable computation time. In our paper, we first review and derive a number of problem properties and, based on these ideas, we develop a constructive heuristic that outperforms the existing constructive heuristics for the problem, providing solutions almost in real-time. Finally, for the cases where extremely high-quality solutions are required, a variable local search algorithm is proposed. The computational experience carried out shows that the algorithm outperforms the best existing metaheuristic for the problem. As a summary, the heuristics presented in the paper substantially modify the state-of-the-art of the approximate methods for the 2-stage assembly scheduling problem with total completion time objective.

Deterministic assembly scheduling problems: A review and classification of concurrent-type scheduling models and solution procedures

Abstract Many activities in industry and services require the scheduling of tasks that can be concurrently executed, the most clear example being perhaps the assembly of products carried out in manufacturing. Although numerous scientific contributions have been produced on this area over the last decades, the wide extension of the problems covered and the lack of a unified approach have led to a situation where the state of the art in the field is unclear, which in turn hinders new research and makes translating the scientific knowledge into practice difficult. In this paper, we propose a unified notation for assembly scheduling models that encompass all concurrent-type scheduling problems. Using this notation, the existing contributions are reviewed and classified into a single framework, so a comprehensive, unified picture of the field is obtained. In addition, a number of conclusions regarding the state of the art in the topic are presented, as well as some opportunities for future research.

Single machine scheduling with periodic machine availability

Abstract In this paper we address the problem of scheduling jobs on a single machine with cyclical machine availability periods. In this problem, the scheduling horizon is composed of periods where the machine is available followed by other periods where no operation can be performed. In the literature, the problem is denoted as scheduling with periodic maintenance, as it is usually assumed that these unavailability periods are employed to perform maintenance activities. Another situation is the one inspiring our research, i.e. the need of completing manufacturing operations within a shift. More specifically, we focus the single machine scheduling problem with makespan objective subject to periodic machine availability. There are several contributions proposing approximate procedures due to the NP-hardness shown for the problem. However, we are not aware of a computational evaluation among these procedures. Furthermore, the problem is similar to the classical bin packing problem, so it is of interest to explore the relation between both problems. In this paper, we address these two issues, and propose new approximate solution procedures for the problem.

The distributed permutation flow shop to minimise the total flowtime

Abstract In the last years, researchers are paying special attention to scheduling in distributed environments due to the increasing benefits of multi-factory manufacture. In this paper, we address the distributed permutation flowshop scheduling problem to minimise the total flowtime. Since, to the best of our knowledge, this problem has not been addressed previously, we first analyse it and discuss several properties, theorems, assignment rules, representation of the solutions and speed-up procedures. Given that the problem is NP-hard, we focus on approximate procedures, and propose eighteen constructive heuristics to obtain high-quality solutions in reasonable CPU times. In addition, we propose an iterative improvement algorithm to further refine the so-obtained solutions. The extensive computational experience carried out shows that the proposed method outperforms several metaheuristics adapted from related scheduling problems.

Available-to-promise systems in the semiconductor industry: a review of contributions and a preliminary experiment

This paper focuses on Available-To-Promise (ATP) systems in the semiconductor industry. These systems have been successfully applied in a number of sectors, although it is often mentioned that their advantages increase with the ability of obtaining accurate forecasts, and with the possibility of identifying a relatively large number of different customers or customer classes. These conditions do not necessarily fulfil in the semiconductor industry, therefore it is interesting to analyse the few case studies of these systems that have been presented in the literature. A preliminary experiment is carried out using a foundry plant data to investigate the influence of the forecast accuracy and forecast bias in the performance of these systems. The results highlight the problems caused by the lack of homogeneity in the forecast, and the distortion introduced by customers ‘inflating’ their projected demand in order to ensure a higher share of the orders.