A heuristic model for the sequence-dependent lot scheduling problem

This paper presents a heuristic algorithm for finding a good solution for the sequence-dependent lot scheduling problem. Unlike available methods, the algorithm eliminates the need for creating new artificial problems and implementing feasibility tests. It also eliminates the tedious task of translating setup relationships into a mathematical programming formulation. The result is a conceptually simple solution technique that is practically motivated and easily implemented for use on the shop floor. Comparison of algorithm performance with published results demonstrates the efficacy of the approach.     

A stochastic programming model for outpatient appointment scheduling considering unpunctuality

Many papers on outpatient appointment scheduling assume that patients arrive on time. However, unpunctuality is a stochastic factor that is inevitable in practice, which leads to patients arriving out of order. A schedule may not be reasonable if a clinic neglects the influence of patient unpunctuality. This paper addresses the outpatient scheduling problem considering unpunctuality (OS-U) by developing a stochastic programming model. We compare the performance of the OS-U system with the strict-punctuality (OS-P) system. We illustrate that the model has an exact and unified formula for cases of patients arriving in the appointment order and arriving out of order. The OS-U problem is solved by using Benders decomposition combined with the sample average approximation (BD-SAA) technique to determine the global optimal set of appointment intervals with the goal of minimizing the weighted sum of all patient waiting times, doctor idle times, and overtime. Numerical experiments indicate that the appointment rule changes when considering unpunctuality, although the set of optimal appointment intervals still takes the shape of dome (interval width increases at first, then remains nearly constant and eventually decreases for the last patients). The OS-P system schedules the first two patients together at the start of a session, whereas the OS-U system schedules them with different appointment times and requires a longer slot between the first two patients if patients tend to arrive early rather than late. The variance of unpunctuality has little impact. The no-show probability has a greater influence on system performances in an OS-U system than those in an OS-P system.     

A flight scheduling model for Taiwan airlines under market competitions

In this research, we develop a short-term flight scheduling model with variable market shares in order to help a Taiwan airline to solve for better fleet routes and flight schedules in today's competitive markets. The model is formulated as a non-linear mixed integer program, characterized as an NP-hard problem, which is more difficult to solve than the traditional fixed market share flight scheduling problems, often formulated as integer/mixed integer linear programs. We develop a heuristic method to efficiently solve the model. The test results, mainly using the data from a major Taiwan airline's operations, show the good performance of the model and the solution algorithm.     

A heuristic approach to n/ m job shop scheduling: fuzzy dynamic scheduling algorithms

n/m shop scheduling is a ‘ NP-Hard’ problem. Using conventional heuristic algorithms ( priority rules) only, it is almost impossible to achieve an optimal solution. Research has been carried out to improve the heuristic algorithms to give a near-optimal solution. This paper advocates a fuzzy logic based, dynamic scheduling algoridim aimed at achieving this goal. The concept of new membership functions is discussed in die algorithm as a link to connect several priority rules. The constraints to determine the membership function of jobs for a particular priority rule are established, and three membership functions are developed. In order to decide the weight vector of priority rules, an aggregate performance measure is suggested. The methodology for constructing the weight vector is discussed in detail. Experiments have been carried out using a simulation technique to validate the proposed scheduling algorithm.     

Flow shop scheduling by transportation model

This paper describes the classical problem of scheduling n jobs on m machines in a flow shop. A schedule evaluation algorithm is presented, which for job-pairs, generates a schedule evaluation matrix. The matrix is the input data to a transportation problem, the solution of which gives near-optimal jobsequence and makespan. The performance of the algorithm is discussed.     

Intelligent scheduling model and algorithm for manufacturing

This paper puts forward an intelligent scheduling model based on Hopfield neural network and a unified algorithm for manufacturing. The energy computation function and its dynamic state equation are derived and discussed in detail about their coefficients (parameters) and steps (Delta t) in iteration towards convergence. The unified model is focused on the structure of the above function and equation, in which the goal and penalty items must be involved and meet different schedule models. The applications to different schedule mode including jobshop static scheduling, scheduling with due-date constraint or priority constraint, dynamic scheduling, and JIT (just in time) scheduling are discussed, and a series of examples with Gantt charts are illustrated.     

Constraint-based model for the cyclic multi-hoists scheduling problem

This article presents a method for the resolution of a material handling scheduling problem. The case studied is a real industrial problem. It consists of finding a cyclic schedule for hoist movements in a treatment surface shop. In this kind of facility, several hoists are used for all the handling operations and they have to share common zones. Then it is necessary to control that there is no collision. The mathematical formulation of the problem is based on a combination of disjunctive constraints. The constraints describe either movement schedule or collision avoidance. The resolution procedure presented identifies all the collision configurations and then uses a branch and bound-like algorithm to find the optimal solution of a given problem. The language chosen for our implementation is the constraint logic programming language: Prolog IV, which is able to solve constraints with rational variables. It actively uses the constraint propagation mechanism that can be found in several languages.     

Distributed wireless link scheduling in the SINR model

We present an approximation algorithm for wireless link scheduling under the physical SINR interference model. In the link scheduling problem, it is given a set of \(n\) links in a metric space, each of which is a sender–receiver pair, and the objective is to schedule the links using the minimum amount of time. We focus on a variant of this fundamental problem where the power is fixed, i.e., the power assignment of links is given as part of the input. Specifically, we consider an important category of power assignments called length-monotone sublinear power assignment, which includes the widely studied uniform, mean and linear power assignments. We present a distributed algorithm that can schedule all links in \(O(\log \varDelta (I_{max}+\log ^3n))\) rounds with high probability, where \(\varDelta \) is the ratio between the longest link and the shortest link and \(I_{max}\) is the maximum nearly-equilength class affectance of the link set. It is shown that the proposed algorithm is \(O(\log \varDelta )\) approximate to the optimal schedule in dense networks with \(I_{max}\in \varOmega (\log ^3n)\). To the best of our knowledge, our algorithm is the first distributed one whose approximation ratio is independent of the network size \(n\). Our result also shows that the \(\varOmega (\log n)\) lower bound (Halldórsson and Mitra in: ICALP, 2011) on the approximation ratio does not hold for link sets with \(\log \varDelta \in o(\log n)\).     

A mathematical model for job shop scheduling with multiple process plan consideration per job

In this paper, a mixed integer programming model is formulated for scheduling a set of jobs through a shop when each job is supplied or provided with multiple process plans or process routings. Simultaneous selection of a process plan for each job and the sequencing of the jobs through the machines in the shop based on the set of selected process plans is addressed. The procedure developed seeks to integrate the selection of machines for each job and the sequencing of jobs on each machine based on the objective of minimizing production makespan. the application of the procedure is demonstrated with an example problem. The following conclusions were drawn as a result of the research: (1) the procedure developed produces optimal or near optimal solution; (2) the benefit from the developed approach is that it allows a shop to adaptively select process plans for jobs to optimize on production makespan. By combining solution quality with scheduling flexibility and efficiency, the productivity of a shop can be greatly enhanced.     

A harmony search-based memetic optimization model for integrated production and transportation scheduling in MTO manufacturing

This paper investigates an integrated production and transportation scheduling problem in an MTO supply chain. A harmony search-based memetic optimization model is developed to handle this problem, in which certain heuristic procedures are proposed to convert the investigated problem into an order assignment problem. A novel improvisation process is also proposed to improve the optimum-seeking performance. The effectiveness of the proposed model is validated by numerical experiments. The experimental results show that (1) the proposed model can solve the investigated problem effectively and that (2) the proposed memetic optimization process exhibits better optimum-seeking performance than genetic algorithm-based and traditional memetic optimization processes.     

A two-stage approach for surgery scheduling

A scheduling theory model is applied to study surgery scheduling in hospitals. If a surgical patient is regarded as a job waiting to be processed, and the related surgeons, anesthesiologists, nurses and surgical equipment as machines that are simultaneously needed for the processing of job, then the surgery scheduling can be described as a parallel machines scheduling problem in which a job is processed by multiple machines simultaneously. We adopt the two-stage approach to solve this scheduling problem and develop a computerized surgery scheduling system to handle such a task. This system was implemented in the Shanghai First People’s Hospital and increased the quantity of average monthly finished operations by 10.33 %, the utilization rate of expensive equipment by 9.66 % and the patient satisfaction degree by 1.12 %, and decreased the average length of time that patients wait for surgery by 0.46 day.     

Outpatient appointment scheduling problem considering patient selection behavior: data modeling and simulation optimization

Journal of Combinatorial Optimization - In medical outpatient services, due to patients’ imbalanced selection for doctors of different levels and for different visiting periods, inefficiency...     

Job shop scheduling—A case study

A missile range is essentially a large-scale job-shop, involving prodigious amounts of test equipment and formidable problems of coordination. Because of its characteristics, a missile range can be considered a one-machine, N-job situation. For this problem the major scheduling methods were examined and tested, but all were discarded as unfeasible except one which used a Monte Carlo scheduling procedure adjoined with statistical stopping rules. An algorithm based on these ideas was constructed, and it has proven to be flexible and workable, providing predictably near optimum schedules for the missile range within a probabilistic and statistical framework. Even though there is not total implementation yet, considerable benefits to the missile range have already been experienced. For example, in order to automate the scheduling process, it was necessary to codify the goals of the range, something that had never been formalized before. This involved an unprecedented scrutiny and precision of definition of these goals, and from this study a reasonable numerical optimization criterion was constructed. Also, in order to use any automated scheduling algorithm, data files had to be stored on tape for ready access, which in turn has improved other operations on the missile range that were dependent on these data. Furthermore, the scheduling algorithm is providing conflict-free schedules in a few minutes of computer time.     

A framework for studying practical production scheduling

The aim of this paper is to present what we believe are the most relevant findings and results regarding practical scheduling in order to define practical production scheduling and create a framework that helps researchers to study the various topics that fall under the umbrella of practical production scheduling and to identify the current state of knowledge for each topic. Studies from different fields were analysed and included in this paper, contributing significant knowledge to build a definition of practical production scheduling. Finally, we discuss the applicability that scheduling, as a task, could have in real companies.     

WISCHE: A DSS for water irrigation scheduling

In this paper we present the models and the algorithms which are being used in a decision support system (DSS) to determine water irrigation scheduling. The DSS provides dynamic scheduling of the daily irrigation for a given land area by taking into account the irrigation network topology, the water volume technical conditions and the logistical operations. The system has been validated by the Agriculture Community of Elche (Spain) and annexed to their Supervisory Control and Data Acquisition system (SCADA). We present two heuristic approaches to solve the mixed 0–1 separable nonlinear program for irrigation scheduling implemented with free software.     

A simulated annealing algorithm for job shop scheduling

In this paper, the job shop scheduling problem is considered with the objective of minimization of makespan time. We first reviewed the literature on job shop scheduling using meta-heuristics. Then a simulated annealing algorithm is presented for scheduling in a job shop. To create neighbourhoods, three perturbation schemes, viz. pairwise exchange, insertion, and random insertion are used, and the effect of them on the final schedule is also compared. The proposed simulated annealing algorithm is compared with existing genetic algorithms and the comparative results are presented. For comparative evaluation, a wide variety of data sets are used. The proposed algorithm is found to perform well for scheduling in the job shop.     

A pairwise interchange algorithm for parallel machine scheduling

This paper considers the problem of non-preemptive scheduling n tasks on m identical parallel processors to minimize makespan for simultaneous arrivals. Based on a pairwise interchange method, an efficient algorithm ispresented which is able to give a near-optimal schedule in a short time through suitable pairwise interchange between tasks, after an initial solution is constructed. The behaviour of the algorithm is discussed. Testing results prove its high performance in comparison with available simple heuristic procedures. Finally, the algorithm is generalized for the problems of non-identical processors and non-simultaneous arrivals.     

Satellite downlink scheduling problem: A case study

The synthetic aperture radar (SAR) technology enables satellites to efficiently acquire high quality images of the Earth surface. This generates significant communication traffic from the satellite to the ground stations, and, thus, image downlinking often becomes the bottleneck in the efficiency of the whole system. In this paper we address the downlink scheduling problem for Canada׳s Earth observing SAR satellite, RADARSAT-2. Being an applied problem, downlink scheduling is characterised with a number of constraints that make it difficult not only to optimise the schedule but even to produce a feasible solution. We propose a fast schedule generation procedure that abstracts the problem specific constraints and provides a simple interface to optimisation algorithms. By comparing empirically several standard meta-heuristics applied to the problem, we select the most suitable one and show that it is clearly superior to the approach currently in use.     

Use of a case study in sequencing/scheduling research

This paper describes a study of an industrial sequencing/scheduling problem. The study contains the definition of the problem, data requirements and examination of solution technique. Definition of the problem is discussed from the aspect of uniqueness of the specific system. Discussion of data requirements includes availability and accuracy, while examination of solution technique considers limitation of time, computer capacity, etc., as well as the possibility of imbedding available algorithms into the solution procedure. Conclusions are presented relative to the use of the case study approach in sequencing/scheduling research.