A note: Multi-machine scheduling with general position-based deterioration to minimize total load

The majority of the papers dealing with scheduling deteriorating jobs ignores general deterioration forms, and considers only special cases. Moreover, most of these papers consider deterioration, most of these papers consider deterioration based on job starting times, and only a few study position-based deterioration. Finally, very few researchers focus on the measure of total load, which becomes important in a setting of deterioration on multi-machines. In this note, we study general, non-decreasing, job-dependent and position-dependent deterioration function. The machine setting is parallel identical machines, and the objective function is total load. We introduce a polynomial time solution for this problem.     

Common due-window assignment and scheduling of linear time-dependent deteriorating jobs and a deteriorating maintenance activity

Due-window assignment and production scheduling are important issues in operations management. In this study we investigate the problem of common due-window assignment and scheduling of deteriorating jobs and a maintenance activity simultaneously on a single-machine. We assume that the maintenance duration depends on its starting time. We provide polynomial time solutions for the problem and some of its special cases, where the objective is to simultaneously minimize the earliness, tardiness, due-window starting time, and due-window size costs.     

Land,Structure and Depreciation

We introduce a hedonic price model that enables us to disentangle the value of a property into the value of land and the value of structure. For given reconstruction costs, we are able to estimate the impact of physical deterioration, functional obsolescence and vintage effects on the structure and the impact of time on sale (and external obsolescence) on the land value simultaneously. Our findings show that maintenance has a substantial impact on the rate of physical deterioration. After 50 years of not or barely maintaining a home, a typical structure has lost around 43% of its value. In contrast, maintaining a home very well results in virtually no physical deterioration in the long run.     

Replenish-up-to inventory control policy with random replenishment intervals

The multi period inventory problems have been studied under two main assumptions. Continuous review assumption where an order can be made at any time depending on inventory position and periodic review assumption where an order can be initiated only at discrete time epochs. In this study, we analyze a multi period inventory problem that falls under neither of these two assumptions. In the case we consider, there are periodic replenishments but the replenishment intervals are taken to be i.i.d. random variables. This setting represents the real life cases where a supplier visits a retailer with random inter arrival times and the retailer replenishes his inventories based on a replenish-up-to-level inventory control policy. We also assume that only a certain fraction of unmet demand is backordered and the rest of it is lost.In this setting under general distribution between replenishment epochs, we show the concavity of the expected profit function and give the condition that must hold for the optimal replenish-up-to-level. We also present the specific solutions and analysis under two different distributions, namely, uniform and exponential distributions, together with some numerical examples.     

On a general periodic preventive maintenance policy incorporating warranty contracts and system ageing losses

In this paper, a general periodic preventive maintenance (PM) policy for a repairable revenue-generating system is developed and studied. We define ‘ageing losses’ as the difference in revenues generated by an ideal system (no ageing) and a real system that ages over the same period of consideration. It is assumed that preventive maintenance slows the system deterioration process and therefore reduces ageing losses. The proposed model is general in the sense that (1) both the warranty contracts and system ageing losses are incorporated in the maintenance cost modeling and (2) the implementation of PM actions does not have to be strictly periodic. A cost model is developed for the buyer under two decision variables—the calendar time of the first PM and the degree of each PM. Numerical examples are then presented to show the effectiveness of the proposed model. Sensitivity analyses are further conducted to investigate the impact of model parameters on optimal solutions.     

Quality disclosure when firms set their own quality targets

We investigate how firms adjust their target quality levels when they - or their competitors - become subject to an information disclosure requirement. Our setting is the U.S. airline industry, where all large domestic carriers are required to report their on-time performance (OTP). OTP is measured by comparing a flight’s actual arrival time to its scheduled arrival time, which is chosen by the airline. Therefore, airlines can improve their OTP by simply increasing their scheduled flight times. We study three airlines which become subject to the disclosure requirement and find that they lengthen their schedule times by 1.4 min on average. Moreover, other airlines also increase their schedule times on routes where they compete with newly reporting airlines, by about 2.3 min, while actual flight times remain unchanged. While these numbers are small, the longer schedule times translate into a 15% improvement in OTP for previously reporting airlines. We conclude that newly reporting airlines and their direct competitors adjust their quality targets when they become subject to quality disclosure, which improves their reported quality without improving the actual time that it takes to travel from gate to gate.     

Two-machine flowshop scheduling with a truncated learning function to minimize the makespan

Scheduling with learning effects has continued to attract the attention of scheduling researchers. However, the majority of the research on this topic has been focused on the single-machine setting. Moreover, under the commonly adopted learning model in scheduling, the actual processing time of a job drops to zero precipitously as the number of jobs increases, which is at odds with reality. To address these issues, we study a two-machine flowshop scheduling problem with a truncated learning function in which the actual processing time of a job is a function of the job's position in a schedule and the learning truncation parameter. The objective is to minimize the makespan. We propose a branch-and-bound and three crossover-based genetic algorithms (GAs) to find the optimal and approximate solutions, respectively, for the problem. We perform extensive computational experiments to evaluate the performance of all the proposed algorithms under different experimental conditions. The results show that the GAs perform quite well in terms of both efficiency and solution quality.     

Optimizing capital investments under technological change and deterioration: A case study on MRI machine replacement

ABSTRACT

We study the multiple style and type parallel asset replacement problem (MST-PRES), which determines an optimal policy for keeping or replacing a group of assets that operate in parallel under a limited budget. Operating assets generally suffer from deterioration, which results in high operation and maintenance (O&M) cost and decreased salvage value, and technological improvements make it possible for new assets to operate more efficiently at a lower cost. In order to address these issues, we formulate a multi-objective mixed-integer programming (MIP) model that minimizes fixed and variable costs of purchasing new assets, O&M cost, inventory cost, and penalty cost for unmet demand minus salvage values, while considering technological advances and deterioration as a gain and loss in capacity, respectively. We apply our model to a case study involving two different styles of assets: a full-body magnetic resonance imaging (MRI) machine and a smaller extremity magnetic resonance imaging (eMRI) machine. Each has two types: high-field and low-field. We perform computational experiments and analyses using key model parameters and illustrate optimal replacement strategies considering the impact of technological advances and deterioration. Results show that the proposed MIP model provides valuable insights and strategies for companies, decision makers, and government entities on the capital asset management.     

Scheduling a capacitated single machine with time deteriorating job values

We address the scheduling problem with the following characteristics: (i) there is a single machine available, (ii) the machine has limited capacity, and (iii) job value deteriorates with time. The problem is motivated from several real world situations, such as, downloading process of web pages, and scheduling of multiplexes. Since the problem is NP-hard, we propose new heuristics based on a multiplicative piece-wise metric as an approximation of the slope of job value deterioration. Computational results show that the proposed heuristics perform better than other existing heuristics for similar types of problems.     

Multiple part-type scheduling in flexible robotic cells

This paper considers the scheduling problem arising in two-machine manufacturing cells which repeatedly produce a set of multiple part-types, and where transportation of the parts between the machines is performed by a robot. The cycle time of the cell depends on the robot move sequence as well as the processing times of the parts on the machines. For highly flexible CNC machines, the processing times can be adjusted. To this end, this study tries to find the robot move sequence as well as the processing times of the parts on each machine that jointly minimize the cycle time. The problem of determining the best cycle in a 2-machine cell is first modeled as a traveling salesman problem. Then, an efficient 2-stage heuristic algorithm is constructed and compared with the most common heuristic approach of longest processing time (LPT).     

An inventory model with deteriorating items under inflation when a delay in payment is permissible

This study develops an inventory model for initial-stock-dependent consumption rate when a delay in payment is permissible. In the inventory model, shortages are not allowed. The effect of the inflation rate, deterioration rate, initial-stock-dependent consumption rate and delay in payment are discussed. In the study, mathematical models are also derived under two different circumstances, i.e., Case I: The credit period is less than or equal to the cycle time for settling the account; and Case II: The credit period is greater than the cycle time for settling the account. Besides, expressions for an inventory system's total cost are derived for these two cases. Moreover, a computational procedure and GINO (Lasdon et al., ACM Transactions Mathematical Software 4 (1978) 34–50) are proposed to obtain the optimal order size and cycle time. The results can help managers determine the optimal total cost. Finally, a numerical example demonstrates the applicability of the proposed model.     

Adopting telework: The causal impact of working from home on subjective well-being

We study the impact of work from home (WFH) on subjective well-being during the Covid period, where self-selection of individuals into telework is ruled out, at least part of the time, by stay-at-home orders. We use a difference-in-differences approach with individual fixed effects and identify the specific impact of switching to telecommuting, separately from any other confounding factor. In particular, our identification strategy avoids the influence of interpersonal heterogeneity by exploiting the multiple entries into WFH, by the same individuals, at different times. On average over the period, switching to WFH, especially full-time, worsens mental health. We also find a positive but imprecisely measured impact of part-time WFH on life satisfaction. However, this hides a dynamic evolution, whereby the initial deterioration gives place to an adaptation process after a couple of months. We also uncover a particularly pronounced fall in subjective well-being of women with children, especially in the first months; this could be associated with home-schooling.     

Skilled maintenance trades under lean manufacturing: Evidence from the car industry

This article explores how skilled maintenance trades have fared under lean automotive manufacturing, a cohort of workers relatively neglected in the literature. Historically, such trades possessed a distinct ‘craft consciousness’ derived from apprenticed-acquired skill, autonomy in job execution, strict job boundaries and relative occupational status and prestige. The article assesses how lean has impacted this craft tradition over time, drawing on a case study of one UK car plant to assess its trajectory across three decades. Four different skilled cohorts—electrical, mechanical, control engineers and die maintenance fitters—are examined to gauge respective trends in skill, autonomy, demarcation and status. While the study finds variation in experiences across different trades, the general trend points to a deterioration in work conditions on all four benchmarks of assessment. The article concludes by inferring implications for the future trajectory of skilled trades considering recent accounts provided in Industry 4.0 narratives.     

Maintenance practices in Swedish industries: Survey results

The purpose of this paper is to investigate the maintenance practices that are used in Swedish industry. The study was performed by conducting a cross-sectional survey within Swedish firms that have at least 100 employees. The main results achieved from the study show that the role of maintenance is not highly recognised. There is a need to spend and invest more in maintenance, which is considered by the majority of Swedish industries as a necessary expense. Although about 13% of the maintenance department time is spent on planning maintenance tasks, nevertheless, about one third of the time is spent on unplanned tasks. There is a need for more adoption of maintenance concepts such as total productive maintenance (TPM) and reliability-centred maintenance (RCM). The lack or ineffectiveness of planning and scheduling can significantly restrict the maintenance department in achieving its objectives and can thus prevent the company from maximising business profits and offering competitive advantages.     

A bicriteria approach to maximize the weighted number of just-in-time jobs and to minimize the total resource consumption cost in a two-machine flow-shop scheduling system

We analyze a two-machine flow-shop scheduling problem in which the job processing times are controllable by the allocation of resources to the job operations and the resources can be used in discrete quantities. We provide a bicriteria analysis of the problem where the first criterion is to maximize the weighted number of just-in-time jobs and the second criterion is to minimize the total resource consumption cost. We prove that although the problem is known to be NP-hard even for constant processing times, a pseudo-polynomial time algorithm for its solution exists. In addition, we show how the pseudo-polynomial time algorithm can be converted into a two-dimensional fully polynomial approximation scheme for finding an approximate Pareto solution.     

Order acceptance and scheduling in a two-machine flowshop

We study the order acceptance and scheduling problem in a two-machine flowshop. The firm receives a pool of orders before a planning period, each of which is characterized by revenue, processing times on machines 1 and 2, a due date, and a tardiness penalty. The firm seeks to decide on the orders to accept and schedule the accepted orders so as to maximize the total net revenue. We formulate the problem as mixed-integer linear programming models, and develop a heuristic and a branch-and-bound (B&B) algorithm based on some derived dominance rules and relaxation techniques. We assess the performance of the B&B algorithm and the heuristic via computational experiments. The computational results show that the B&B algorithm can solve problem instances with up to 20 jobs within a reasonable time while the heuristic is efficient in approximately solving large instances of the problem.     

House Search Duration in Hot and Cold Residential Markets

This study analyzes the determinants of house search duration of consumption‐driven buyers and individual investors in different housing market environments. We use data from surveys of recent house‐buyers in “hot” and “cold” housing markets in the 2000s housing bubble in California characterized by rising and declining residential house prices, respectively. The average house price and the surveyed geographical area are the same for both periods. Expected house ownership horizon is shown to be an important determinant of the realized search duration in addition to commonly considered housing and buyer characteristics. We find a statistically significant positive effect of it on the time until purchase in both housing price environments for consumption‐driven buyers. We also find that consumption‐driven house purchases were highly pronounced in coastal areas in the hot market and inland areas in the cold market. In contrast, long‐horizon investment activity leads that of consumption activity in those areas. Short‐horizon investors, on the other hand, concentrated their house search activity in inland areas in both housing market environments.     

The development of post-project buyer–seller interaction in service-intensive projects

The purpose of this research is to enhance the understanding of post-project buyer–seller interaction, a topic previously studied mainly from the perspective of social exchange or sleeping relationships. With the advent of service-intensive projects, however, the dynamics of post-project interaction has changed, demanding a broader theorization. This research extends the scope of project marketing, by proposing a research framework illustrating interaction development in a longitudinal setting. We utilize the framework to analyze three projects, two of which continued for more than a decade, through a qualitative case study. The research provides empirical insight into the interaction orientations and development patterns arising in the post-project stage. It suggests that post-project interaction develops through three main orientations (cooperative development, buyer-led development, and seller-led maintenance) that vary over time, thus creating unique development patterns. The study concludes with five practical recommendations for managers to deal with evolving post-project interaction.     

Timing production in LP models in a rolling schedule

We consider an arbitrary supply chain structure under demand uncertainty. We look at a setting where the supply chain planning is executed periodically and where the demand of end items in subsequent periods is stochastic. In contrast to other linear programming-based approaches, we assume constant planned lead times. In this paper we discuss the timing of production during the planned lead times of items. If production starts immediately, the work-in-process inventory costs are higher, but producing later will result in higher safety stocks. We look at the influence of the demand variation, the planned lead time of the items, the utilization rate of resources, and the added value when merging items, on the inventory costs. The results indicate that, for higher utilization rates, producing early is more suitable.     

基于活动分割的资源优化研究

在假定活动可分割的基础上,针对资源波动问题,提出了一个基于遗传算法的资源优化方法.首先在已知活动工期的基础上,确定项目工期,继而确定关键工序和非关键工序,并利用基于二元表示的遗传算法,对每个可分的非关键活动在其ES(最早开始时间)到LF(最迟结束时间)的范围内进行调整,以优化资源分配.最后引用一个示例,表明了提出的方法在资源优化方面的优越性.