Project Scheduling—Theory and Practice

The project scheduling problem involves the scheduling of project activities subject to precedence and/or resource constraints. Of obvious practical importance, it has been the subject of intensive research since the late fifties. A wide variety of commercialized project management software packages have been put to practical use. Despite all these efforts, numerous reports reveal that many projects escalate in time and budget and that many project scheduling procedures have not yet found their way to practical use. The objective of this paper is to confront project scheduling theory with project scheduling practice. We provide a generic hierarchical project planning and control framework that serves to position the various project planning procedures and discuss important research opportunities, the exploration of which may help to close the theory‐practice gap.     

Genetic algorithm to production planning and scheduling problems for manufacturing systems

Fundamental and extended multi-objective (MO) models are designed to address earliness/tardiness production scheduling planning (ETPSP) problems with multi-process capacity balance, multi-product production and lot-size consideration. A canonical genetic algorithm (GA) approach and a prospective multi-objective GA (MOGA) approach are proposed as solutions for different practical problems. Simulation results as well as comparisons with other techniques demonstrate the effectiveness of the MOGA approach, which is a noted improvement to any of the existing techniques, and also in practice provides a new trend of integrating manufacturing resource planning (MRPII) with just-in-time (JIT) in the production planning procedure.     

The permutation flow shop problem with just in time production considerations

This research presents a variation to the permutation flow shop problem where Just In Time (JIT) production requirements are taken into account. The model developed in this research employs dual objectives. In addition to the traditional objective of minimizing the production makespan, minimization of Miltenburg's material usage rate is also incorporated. In this model, multiple units of any product are permitted in the production sequence. However, the minimization of material usage rates attempts to prevent batch scheduling of products and allows unit flow of products as required in demand flow manufacturing. A solution method is proposed for determining an optimal production sequence via an efficient frontier approach and Simulated Annealing (SA). Test problems and specific performance criteria are used to assess the solutions generated by the proposed method. Experimental results presented in this paper show that the use of the efficient frontier and SA provide solutions that approach the optimal solution for the performance measures used in this research.     

Tactical production and distribution planning with dependency issues on the production process

Tactical production-distribution planning models have attracted a great deal of attention in the past decades. In these models, production and distribution decisions are considered simultaneously such that the combined plans are more advantageous than the plans resolved in a hierarchical planning process. We consider a two-stage production process, where in the first stage raw materials are transformed into continuous resources that feed the discrete production of end products in the second stage. Moreover, the setup times and costs of resources depend on the sequence in which they are processed in the first stage. The minimum scheduling unit is the product family which consists of products sharing common resources and manufacturing processes. Based on different mathematical modelling approaches to the production in the first stage, we develop a sequence-oriented formulation and a product-oriented formulation, and propose decomposition-based heuristics to solve this problem efficiently. By considering these dependencies arising in practical production processes, our model can be applied to various industrial cases, such as the beverage industry or the steel industry. Computation tests on instances from an industrial application are provided at the end of the paper.     

Honoring complexity in sustainable supply chain research: a rough set theoretic approach (SI:ResMeth)

Abstract

Sustainable supply chain management (SSCM) faces greater complexity because it considers additional stakeholder requirements, broader sustainable performance objectives, increased sustainable business practices and technologies, and relationships among those entities. These additional complexities make SSCM more difficult to manage and operate than traditional supply chains. Complex systems require new methods for research especially given reductionist research paradigms of modern science. Rough set theory (RST) can be a valuable tool that will help address complexity in SSCM research and practice. To exemplify RST usefulness and applicability, an illustrative application using sustainable supply chain practices (SSCP), and environmental and economic performance outcomes is introduced. The conceptual case provides nuanced insights for researchers and practitioners in mitigating and evaluating various SSCM complexities. RST limitations and extensions are introduced.     

Supply Chain Scheduling: Distribution Systems

We study conflict and cooperation issues arising in a supply chain where a manufacturer makes products which are shipped to customers by a distributor. The manufacturer and the distributor each has an ideal schedule, determined by cost and capacity considerations. However, these two schedules are in general not well coordinated, which leads to poor overall performance. In this context, we study two practical problems. In both problems, the manufacturer focuses on minimizing unproductive time. The distributor minimizes customer cost measures in the first problem and minimizes inventory holding cost in the second problem. We first evaluate each party's conflict, which is the relative increase in cost that results from using the other party's optimal schedule. Since this conflict is often significant, we consider several practical scenarios about the level of cooperation between the manufacturer and the distributor. These scenarios define various scheduling problems for the manufacturer, the distributor, and the overall system. For each of these scheduling problems, we provide an algorithm. We demonstrate that the cost saving provided by cooperation between the decision makers is usually significant. Finally, we discuss the implications of our work for how manufacturers and distributors negotiate, coordinate, and implement their supply chain schedules in practice.     

Is the scheduling task context-dependent? A survey investigating the presence of constraints in different manufacturing contexts

Abstract

Most studies regarding real scheduling constraints only consider the constraints related to the specific manufacturing environment studied, limiting the possibility of drawing general conclusions. A survey of 50 companies was conducted in order to discover which constraints were present and what their relationship was with the scheduling context. This paper investigates which practical scheduling constraints are present in the manufacturing industry and whether the scheduling task is context-dependent. Results of this study show that some practical production constraints are context-dependent.     

Planning and Scheduling in Supply Chains: An Overview of Issues in Practice

This paper gives an overview of the theory and practice of planning and scheduling in supply chains. It first gives an overview of the various planning and scheduling models that have been studied in the literature, including lot sizing models and machine scheduling models. It subsequently categorizes the various industrial sectors in which planning and scheduling in the supply chains are important; these industries include continuous manufacturing as well as discrete manufacturing. We then describe how planning and scheduling models can be used in the design and the development of decision support systems for planning and scheduling in supply chains and discuss in detail the implementation of such a system at the Carlsberg A/S beerbrewer in Denmark. We conclude with a discussion on the current trends in the design and the implementation of planning and scheduling systems in practice.     

What makes leadership,leadership? Using self-expansion theory to integrate traditional and contemporary approaches

Numerous traditional theories and paradigms of leadership purport to describe what leadership is. It is difficult to reconcile these traditional approaches, however, if each one alone, independent of the others, is viewed as capturing the actual identity of leadership. In this article, we take an integrative view of traditional approaches to leadership. To do so, we first identify some underlying ideas common to them. Next, we explain how these underlying ideas lead us to a fundamental theory about close relationships—that is, self-expansion theory, which refers to a psychological process in which an individual incorporates another into the self (Aron & Aron, 1986). We then review the traditional leadership theories to explore whether these theories may be linked through self-expansion theory and whether self-expansion may help to explain why boundary conditions have been discovered for all of them. In this process, we explore whether traditional approaches to leadership might also be linked with more contemporary approaches through self-expansion theory. Finally, we discuss the implications for future research and professional practice of the integration of traditional approaches to leadership.     

Development and implementation of a knowledge-based system for the dynamic scheduling of a two-stage production process

Abstract

This paper discusses the implementation of a knowledge-based system for the dynamic scheduling of a two-stage production process. It is an interactive, real-time, menu-driven system written in Prolog. The system architecture is delineated and the rules and problem-solving logic to be used under various dynamic situations are described. Results of a sample system test session are included to illustrate its use.     

Dynamic scheduling of manufacturing job shops using extreme value theory

Most job shop scheduling approaches reported in the literature assume that the scheduling problem is static (i.e. job arrivals and the breakdowns of machines are neglected) and in addition, these scheduling approaches may not address multiple criteria scheduling or accommodate alternate resources to process a job operation. In this paper, a scheduling method based on extreme value theory (SEVAT) is developed and addresses all the shortcomings mentioned above. The SEVAT approach creates a statistical profile of schedules through random sampling, and predicts the quality or 'potential' of a feasible schedule. A dynamic scheduling problem was designed to reflect a real job shop scheduling environment closely. Two performance measures, viz. mean job tardiness and mean job cost, were used to demonstrate multiple criteria scheduling. Three factors were identified, and varied between two levels each, thereby spanning a varied job shop environment. The results of this extensive simulation study show that the SEVAT scheduling approach produces a better performance compared to several common dispatching rules.     

Scheduling two job families on a single machine with two competitive agents

We consider the scheduling problems arising when two agents, each with a family of jobs, compete to perform their respective jobs on a single machine. A setup time is needed for a job if it is the first job to be processed on the machine or its processing on the machine follows a job that belongs to another family. Each agent wants to minimize a certain cost function, which depends on the completion times of its jobs only. The aim is to find a schedule for all the jobs of the two agents that minimizes the objective of one agent while keeping the objective of the other agent being bounded by a fixed value \(Q\). Polynomial-time and pseudo-polynomial-time algorithms are designed to solve the problem involving various combinations of regular scheduling objective functions.     

Minimizing tardiness on a single processor with sequence-dependent setup times: a simulated annealing approach

In today's fast-paced Just-In-Time and mass customization manufacturing in a sequence-dependent setup environment, the challenge of making production schedules to meet due-date requirements is becoming a more complex problem. Unfortunately, much of the research on operations scheduling problems has either ignored setup times or assumed that setup times on each machine are independent of the job sequence. This paper considers the problem of minimizing tardiness, a common measure of due-date performance, in a sequence-dependent setup environment. Simulated annealing was used to solve the sequencing problem, and its performance was compared with random search. Our experimental results show that the algorithm can find a good solution fairly quickly, and thus can rework schedules frequently to react to variations in the schedule. The algorithm is invaluable for ‘on-line’ production scheduling and ‘last-minute’ changes to production schedule. The results of this research also suggest ways in which more complex and realistic job shop environments, such as multiple machines with a higher number of jobs in the sequence, and other scheduling objectives can be modeled. This research also investigates computational aspects of simulated annealing in solving complex scheduling problems.     

Bridging Practice and Theory: A Design Science Approach

Despite ambitious efforts in various fields of research over multiple decades, the goal of making academic research relevant to the practitioner remains elusive: theoretical and academic research interests do not seem to coincide with the interests of managerial practice. This challenge is more fundamental than knowledge transfer, it is one of diverging knowledge interests and means of knowledge production. In this article, we look at this fundamental challenge through the lens of design science, which is an approach aimed primarily at discovery and problem solving as opposed to accumulation of theoretical knowledge. We explore in particular the ways in which problem‐solving research and theory‐oriented academic research can complement one another. In operations management (OM) research, recognizing and building on this complementarity is especially crucial, because problem‐solving–oriented research produces the very artifacts (e.g., technologies) that empirical OM research subsequently evaluates in an attempt to build explanatory theory. It is indeed the practitioner—not the academic scientist—who engages in basic research in OM. This idiosyncrasy prompts the question: how can we enhance the cross‐fertilization between academic research and research practice to make novel theoretical insights and practical relevance complementary? This article proposes a design science approach to bridge practice to theory rather than theory to practice.     

客户时间窗变化的物流配送干扰管理模型——基于行为的视角

针对客户时间窗变化而导致的物流配送难以顺利实施这一难题,运用干扰管理思想,以提高物流配送干扰管理决策过程的科学性为目标,结合行为科学中对人的行为感知的研究方法与运筹学中定量的研究手段,分析客户时间窗变化这类干扰事件对客户、物流配送运营商和配送业务员等受扰主体的影响,研究基于行为的扰动度量方法, 构建客户时间窗变化的字典序多目标干扰管理模型,并给出快速高效的求解方法。实例结果表明:本文方法比已有的全局重调度方法和局部重调度方法更实用--能够均衡各方的利益,获得扰动最小的调整方案。     

A study of expediting practices in manufacturing firms

Abstract

This paper presents the results of an empirical investigation of one of the most common yet least optimized production management practices—expediting. The intention of this study was to generate quantitative insight into issues that underlie expediting decision making, such as the relative frequency of various causes of expediting, commonly used expediting strategies and tactics, and the interaction of expediting and the production scheduling environment in use. The study centered around a survey sent to 1768 manufacturing staff personnel, with 182 usable questionnaires returned. It is hoped that the data and conclusions presented in this paper will be of use to production management researchers who are interested in expediting as a managerial decision.     

Comparative evaluation of genetic algorithms for job-shop scheduling

Many optimization problems from the industrial engineering world, in particular the manufacturing systems, are very complex in nature and quite hard to solve by conventional optimization techniques. There has been increasing interest in imitating living beings to solve such kinds of hard optimization problems. Simulating the natural evolutionary process of human beings results in stochastic optimization tech niques called evolutionary algorithms, which can often outperform conventional optimization methods when applied to difficult real-world problems. There are currently three main avenues of this research: genetic algorithms (GAs), evolutionary programming (EP) and evolution strategies (ESs). Among them, genetic algorithms are perhaps the most widely known types of evolutionary algorithms today. During the past years, several GAs for the job-shop scheduling problems have been proposed, each with different chromosome representation. In this paper, the different GAs are collected from the literature and an attempt has been made to evaluate them. The benchmark problems available in open literature are used for evaluation and the performance measure considered is makespan. The algorithms are coded in C+ +.     

Simulation-based production schedule generation

Abstract

While simulation has been used in manufacturing for many years, predominantly for facility design, it is within the last few years, that simulation languages have been developed to a point where they can be used on a day-to-day basis to generate schedules and predict their performance. This paper describes our use of different modelling techniques to develop a production schedule generation system. An example describing a system for a small- to medium-sized order producing company using SIMAN/CINEMA is included. While addressing the shortcomings of existing scheduling systems it is shown how the approach taken is a feasible way of creating a dynamic goal-driven simulation-based production scheduler. The paper does not aim to describe an ‘off the shelf’ scheduling system product, but rather to give an overview to methods, techniques and experiences which enable us rapidly to tailor a simulation-based scheduling system to the specific needs of a company.     

SCHEDULING PARALLEL PROCESSORS WITH SETUP COSTS AND RESOURCE LIMITATIONS

An integer linear programming model is presented for the scheduling of n products on m identical machines. The particular problem studied is one that occurs frequently in the fiberglass and textile industries. The model incorporates setup costs, lost production costs, and overtime costs. Due to the structure of the model, integer solutions can be obtained by explicitly restricting only a small number of the integer variables. This allows those responsible for scheduling to solve realistically sized problems in an efficient manner. Computational results are provided for a set of generated test problems.     

A digital pedagogy pivot: re-thinking higher education practice from an HRD perspective

ABSTRACT

This paper has a provocative purpose. From both HRD and academic practice perspectives, it considers the digital pedagogy pivot made necessary by the Covid-19 pandemic. Universities have traditionally resisted substantial change in learning and teaching processes. This paper addresses the challenge they face of achieving the equivalent of a ten-year digital learning strategy in mere months. From a position that HE pedagogy constitutes a site of HRD practice, the paper considers the characteristics of a meaningful, digitally enabled pedagogy in Higher Education (HE) and their alignment with established HRD theories and concepts. It considers the pedagogic opportunities arising from the ‘digital pivot’ and the HRD processes appropriate to facilitate game-changing approaches to academic practice in Higher Education. The paper advances debate about the relationship between HRD and HE academic practice and contributes proposals for HRD processes to support rapid pedagogic change. It further contributes an original categorization of the way in which HRD concepts and theories are aligned with principles of HE pedagogy and a digital pedagogy pivot model.