JournalTOCs

Flexible Services and Manufacturing Journal
Journal Prestige (SJR): 1.633

Citation Impact (citeScore): 3
Number of Followers: 2

Hybrid journal (It can contain Open Access articles)
ISSN (Print) 1936-6582 - ISSN (Online) 1936-6590
Published by Springer-Verlag

[2469 journals]

Modeling and data analytics in manufacturing and supply chain operations
- Free pre-print version: Loading...
  Rate this result: What is this?
  
  Please help us test our new pre-print finding feature by giving the pre-print link a rating.
  A 5 star rating indicates the linked pre-print has the exact same content as the published article.
  
  PubDate: 2022-06-01
Information sharing in decentralised supply chains with partial
collaboration
- Free pre-print version: Loading...
  Rate this result: What is this?
  
  Please help us test our new pre-print finding feature by giving the pre-print link a rating.
  A 5 star rating indicates the linked pre-print has the exact same content as the published article.
  
  Abstract: Abstract We explore the value of information sharing for smoothing the dynamics of supply chains when some echelons do not collaborate. To this end, we study seven information sharing structures in a four-echelon supply chain using a system dynamics approach. We find that the overall propagation of the bullwhip effect in supply chains decreases as the number of echelons sharing information grows, but it is not dependent on their position. Nonetheless, the performance of the echelons strongly relies on the degree of downstream collaboration; therefore, information sharing in the lower nodes has a higher impact on the overall supply chain costs. We also investigate the benefits of adding new members to the collaborative strategy in different lead-time scenarios. Finally, we provide managerial recommendations for decentralised supply chains.
  PubDate: 2022-06-01
Leasing or selling' The channel choice of durable goods manufacturer
considering consumers’ capital constraint
- Free pre-print version: Loading...
  Rate this result: What is this?
  
  Please help us test our new pre-print finding feature by giving the pre-print link a rating.
  A 5 star rating indicates the linked pre-print has the exact same content as the published article.
  
  Abstract: Abstract In this paper, we explore how a monopoly manufacturer chooses the market strategies and decides the optimal price to obtain maximum profit. We divide the market into the C-type market and the N-type market, and analyze the profitability of the monopoly manufacturer who takes the pure-selling, pure-leasing and hybrid strategy respectively, considering consumers’ capital constraint and the life span of the durable goods in an indefinite time horizon model. (1) We find that a larger proportion of the consumers with capital constraint has a more significant impact on the prices and it could slow down the development of the rental market. When the scale of the group attains up to a threshold level, it would greatly influence the customers’ demand and their marketing strategy, and encourages more manufacturers to take the leasing strategy. (2) In the Hybrid Strategy, we see explicit growth in the overall profit with both the leasing channel and the selling channel working together, although the former outperforms the latter. The suppressed selling channel, in fact, has to lower the price to keep the market coverage, with an independent market structure. (3) Finally, we find that a leasing agent may help the manufacturer at first and then become a tough competitor. These findings provide new insights for the operation of large construction machinery manufacturing companies. subject classification numbers as needed.
  PubDate: 2022-06-01
Integrated production and maintenance planning under uncertain demand with
concurrent learning of yield rate
- Free pre-print version: Loading...
  Rate this result: What is this?
  
  Please help us test our new pre-print finding feature by giving the pre-print link a rating.
  A 5 star rating indicates the linked pre-print has the exact same content as the published article.
  
  Abstract: Abstract Strong interactions between decisions in the maintenance and production scheduling domains, and their impacts on the equipment yield rates necessitate maintenance and production decisions being optimized concurrently, with considerations of yield dependencies on the equipment conditions and production rates. This paper proposes an integrated decision-making policy for production and maintenance operations on a single machine under uncertain demand, with concurrent considerations and learning of yield dependencies on the equipment conditions and production rates. This policy is obtained through a two-stage stochastic programming model, which considers the variable demand, machine degradation, and maintenance times. This model incorporates outsourcing decisions and operational decisions regarding reworking, scraping of imperfect products to ensure the demand is adequately met. A closed-form reinforcement learning method is utilized to learn yield dependencies. Simulations confirm the necessity of yield learning and show the proposed method outperforms the traditional, fragmented approaches where the effects of production rates and machine conditions on the resulting yield rates are not considered. The two-stage stochastic setting is demonstrated by comparing with the traditional one-stage deterministic approach, where decisions are made based on the expected demand and production performance, with scrapping, reworking, and outsourcing decisions established before the demand and production performance are observed.
  PubDate: 2022-06-01
Integrated optimization on production scheduling and imperfect preventive
- Free pre-print version: Loading...
  Rate this result: What is this?
  
  Please help us test our new pre-print finding feature by giving the pre-print link a rating.
  A 5 star rating indicates the linked pre-print has the exact same content as the published article.
  
  Abstract: Abstract This paper proposes a multi-objective integrated optimization model of production scheduling and machine maintenance to find the optimal production sequence and preventive maintenance (PM) decisions. This model considers the setup time, the learning-forgetting effects and the multi-degradation effects. The setup time and the learning-forgetting effects are associated with jobs' similarities and PM decisions. The multi-degradation effects including machine deterioration, failure rate and quality characteristic loss determine the stochastic nature of the objectives. A hybrid maintenance strategy combining imperfect PM and minimal repair (MR) is adopted to effectively reduce the failure frequency and improve the processing quality. Then, the multi-objective solution is simplified by normalizing cost, time and utilization. The local search and the elitism strategy are conducted to avoid the solutions falling into local optimum and losing the best chromosome during evolutions. Finally, a case study of automobile engine manufacturing shows that our proposed model can reduce the total maintenance costs by 27%, shorten the total processing time by 3%, as well as improve the machine utilization by 3%.
  PubDate: 2022-06-01
A new method for a class of parallel batch machine scheduling problem
- Free pre-print version: Loading...
  Rate this result: What is this?
  
  Please help us test our new pre-print finding feature by giving the pre-print link a rating.
  A 5 star rating indicates the linked pre-print has the exact same content as the published article.
  
  Abstract: Abstract This paper studies the scheduling problem of jobs with release times, non-identical sizes, and incompatible job families on unrelated parallel batch machines. The capacities of batch machines and the processing times of each job on the batch machines are different. The processing time of one batch is equal to the longest processing time of jobs in this batch. Different types of jobs are not allowed to be assigned into the same batch, which is known as incompatible job families. Mixed integer linear programming and constraint programming (CP) models are proposed. A new batch-based local search method is designed and an iterated greedy (IG) algorithm is developed to avoid unreasonable exchanging of jobs during the local search. Numerical results show that the CP method can obtain high quality solutions in the small-scale instances. For the large-scale instances, the IG algorithm with the new local search method has a competitive performance.
  PubDate: 2022-06-01
Robust scheduling and dispatching rules for high-mix collaborative
manufacturing systems
- Free pre-print version: Loading...
  Rate this result: What is this?
  
  Please help us test our new pre-print finding feature by giving the pre-print link a rating.
  A 5 star rating indicates the linked pre-print has the exact same content as the published article.
  
  Abstract: Abstract Motivated by the increasing demand of mass customisation in production systems, this paper proposes a robust and adaptive scheduling and dispatching method for high-mix human-robot collaborative manufacturing facilities. Scheduling and dispatching rules are derived to optimally track the desired production within the mix, while handling uncertainty in job processing times. The sequencing policy is dynamically adjusted by online forecasting the throughput of the facility as a function of the scheduling and dispatching rules. Numerical verification experiments confirm the possibility to accurately track highly variable production requests, despite the uncertainty of the system.
  PubDate: 2022-06-01
Anticipatory approach for dynamic and stochastic shipment matching in
hinterland synchromodal transportation
- Free pre-print version: Loading...
  Rate this result: What is this?
  
  Please help us test our new pre-print finding feature by giving the pre-print link a rating.
  A 5 star rating indicates the linked pre-print has the exact same content as the published article.
  
  Abstract: Abstract This paper investigates a dynamic and stochastic shipment matching problem faced by network operators in hinterland synchromodal transportation. We consider a platform that receives contractual and spot shipment requests from shippers, and receives multimodal services from carriers. The platform aims to provide optimal matches between shipment requests and multimodal services within a finite horizon under spot request uncertainty. Due to the capacity limitation of multimodal services, the matching decisions made for current requests will affect the ability to make good matches for future requests. To solve the problem, this paper proposes an anticipatory approach which consists of a rolling horizon framework that handles dynamic events, a sample average approximation method that addresses uncertainties, and a progressive hedging algorithm that generates solutions at each decision epoch. Compared with the greedy approach which is commonly used in practice, the anticipatory approach has total cost savings up to 8.18% under realistic instances. The experimental results highlight the benefits of incorporating stochastic information in dynamic decision making processes of the synchromodal matching system.
  PubDate: 2022-06-01
Performance optimization of supply chain based on cooperative contract
with disappointment-aversion strategic consumers
- Free pre-print version: Loading...
  Rate this result: What is this?
  
  Please help us test our new pre-print finding feature by giving the pre-print link a rating.
  A 5 star rating indicates the linked pre-print has the exact same content as the published article.
  
  Abstract: Abstract Consumers’ strategic behavior and psychological perception have impact on supply chains. In this paper, we consider a supply chain with one supplier and one retailer to study the influence of disappointment-aversion strategic (DAS) consumers on supply chain members’ decisions and performance. The results of this study show that strategic consumers can reduce the profit levels of such a supply chain, whilst DAS consumers can alleviate this effect. We also study the effectiveness of a quantity commitment strategy for a centralized supply chain when faced with DAS consumers. Under certain conditions, the quantity commitment strategy can further reduce the loss of profit caused by strategic consumers. Then the maximum profit of the centralized supply chain under the quantity commitment strategy is used as a benchmark. We then analyze the coordination efficiency and implementability of a wholesale price contract and a price subsidy contract respectively in a decentralized supply chain. The results show that the wholesale price contract can achieve the optimal profit benchmark of the centralized supply chain, but it can only realize fixed profit allocation to supply chain members; the price subsidy contract can not only achieve the optimal profit of the centralized supply chain but also make arbitrary profit allocation among chain members.
  PubDate: 2022-06-01
A data-driven multi-fidelity simulation optimization for medical staff
configuration at an emergency department in Hong Kong
- Free pre-print version: Loading...
  Rate this result: What is this?
  
  Please help us test our new pre-print finding feature by giving the pre-print link a rating.
  A 5 star rating indicates the linked pre-print has the exact same content as the published article.
  
  Abstract: Abstract Overcrowding at emergency departments in Hong Kong has been a critical issue for hospital managers recently. In this study, we focus on optimizing the medical staff configuration to alleviate overcrowding. According to the service requirements proposed by the Hong Kong government, 90% of urgent patients should receive treatment within 30 min. However, this condition is rarely satisfied in the practical situation. Therefore, we formulate the problem as minimizing the proportion of urgent patients that violate the service requirements while satisfying the service requirements of the other categories and cost constraints, thereby resulting in an optimization problem with a stochastic objective and several stochastic constraints. To solve this problem efficiently, we proposed a multi-fidelity simulation optimization framework containing a low- and a high-fidelity process. We utilize an evolutionary algorithm with violation-constrained handling assisted by a surrogate model as a low-fidelity process to shrink the solution space and generate an elite population. In the high-fidelity process, we exploit the optimal computing budget allocation method to identify the best solution in the elite population based on a data-driven simulation model. A case study is also discussed, and the results demonstrated that with a limited labor cost, there is a 52.05% reduction on average in the waiting time of urgent patients. Meanwhile, our proposed multi-fidelity simulation optimization framework proves to save 98.4% of the simulation time.
  PubDate: 2022-06-01
A real options approach to value manufacturing flexibilities with
regime-switching product demand
- Free pre-print version: Loading...
  Rate this result: What is this?
  
  Please help us test our new pre-print finding feature by giving the pre-print link a rating.
  A 5 star rating indicates the linked pre-print has the exact same content as the published article.
  
  Abstract: Abstract This research is motivated by a real industry problem. A manufacturer produces two different types of products. The manufacturer has two alternatives to invest: fixed capacity systems, one for each type of product, or invest in a flexible system simultaneously producing both types of products. To this end, the value of flexibility has to be determined to justify the investment in the flexibility system. When valuing manufacturing flexibility to model demand uncertainty, most of the existing literature is built on the assumption that demand for a product will grow indefinitely. This assumption, however, ignores the reality that demand for a product often grows initially, then levels out, and finally falls off. To investigate how this nonstationarity in demand growth affects the value of flexibility, we consider a manufacturing system having three types of manufacturing flexibilities (expansion, contraction, and switching) and producing two types of products with correlated demands. Each type of product is assumed to have two demand regimes: a growth regime representing the demand increases initially and a decay regime representing the demand decreases subsequently. A lattice approach is developed to discretize the evolution of the correlated demands of both products and a dynamic programming-based model is used to value flexibilities. Results show that ignoring the two demand regimes undervalues contraction, switching, and total flexibilities; but overvalues expansion flexibility. It is very common that many sectors, such as automobile and semiconductor, produce products simultaneously. Hence, the findings may help decision-makers understand the inherent values of flexibilities under different demand shifting patterns.
  PubDate: 2022-04-27
Correction to: Robust multi-period capacity, location, and access of rural
cardiovascular services under uncertainty
- Free pre-print version: Loading...
  Rate this result: What is this?
  
  Please help us test our new pre-print finding feature by giving the pre-print link a rating.
  A 5 star rating indicates the linked pre-print has the exact same content as the published article.
  
  PubDate: 2022-04-26
DSS approach for sustainable system design of shuttle-based storage and
retrieval systems
- Free pre-print version: Loading...
  Rate this result: What is this?
  
  Please help us test our new pre-print finding feature by giving the pre-print link a rating.
  A 5 star rating indicates the linked pre-print has the exact same content as the published article.
  
  Abstract: Abstract Automated warehousing systems need to balance operational efficiency, energy consumption and overall system cost in sustainable supply chains. This paper presents an analytical model-based Decision Support System (DSS) for sustainable system design of Shuttle-Based Storage and Retrieval System (SBS/RS). Multiple system design indicators, namely mean service time, mean energy consumption, and overall system cost, are considered in a mathematical model. A simulation model is developed to validate the accuracy of the mathematical model. Extensive numerical experiments explore the impacts of rack design and equipment operating parameters on various system performance indicators and summarize balanced equipment operating settings. Overall, this study provides an analytical-model based DSS on sustainable SBS/RS configurations for decision-making managers and system designers.
  PubDate: 2022-03-29
Anticipating technical car sequencing rules in the master production
scheduling of mixed-model assembly lines
- Free pre-print version: Loading...
  Rate this result: What is this?
  
  Please help us test our new pre-print finding feature by giving the pre-print link a rating.
  A 5 star rating indicates the linked pre-print has the exact same content as the published article.
  
  Abstract: Abstract In this paper, we propose a new linear programming-based approach that enables the consideration of technical car sequencing rules in the master production scheduling of mixed-model assembly lines at a much higher level of detail than previous approaches. To this end, we investigate certain interdependencies of car sequencing rules, which have largely been neglected, both in practice and in the research literature. We illustrate the existence and impact of these interdependencies and show that they induce additional implicit constraints, which can be represented by linear inequalities and incorporated into linear optimization models for master production scheduling. In a numerical study, we evaluate the approach and show, that it can significantly reduce sequencing violations compared to existing approaches.
  PubDate: 2022-03-03
  DOI: 10.1007/s10696-021-09443-6
Addressing consistency and demand uncertainty in the Home Care planning
problem
- Free pre-print version: Loading...
  Rate this result: What is this?
  
  Please help us test our new pre-print finding feature by giving the pre-print link a rating.
  A 5 star rating indicates the linked pre-print has the exact same content as the published article.
  
  Abstract: Abstract Optimizing Home Care Services is receiving a great attention in Operations Research. We address arrival time consistency, person-oriented consistency and demand uncertainty in Home Care, while jointly optimizing assignment, scheduling and routing decisions over a multiple-day time horizon. Consistent time schedules are very much appreciated by patients who, in this setting, are very sensitive to changes in their daily routines. Also person-oriented consistency positively impacts on service quality, guaranteeing that almost the same set of caregivers take care of a patient in the planning horizon. Demand uncertainty plays a pivotal role, too, since both the set of patients under treatment and their care plan can change over time. To the best of our knowledge, this is the first paper dealing with all these aspects in Home Care via a robust approach. We present a mathematical model to the problem, and a pattern-based algorithmic framework to solve it. The framework is derived from the model via decomposition, i.e. suitably fixing the scheduling decisions through the concept of pattern. We propose alternative policies to generate patterns, taking into account consistency and demand uncertainty; when embedding them in the general framework, alternative pattern based algorithms originate. The results of a rich computational experience show that introducing consistency and demand uncertainty in pattern generation policies is crucial to efficiently compute very good quality solutions, in terms of robustness and balancing of the caregiver workload. In addition, a comparison with a simpler model, where no kind of consistency is imposed, shows the importance of considering consistency in pursuing a valuable patient-centered perspective, with a positive effect also on the efficiency of the solution approach.
  PubDate: 2022-03-01
  DOI: 10.1007/s10696-021-09412-z
Integrating preventive maintenance to two-stage assembly flow shop
scheduling: MILP model, constructive heuristics and meta-heuristics
- Free pre-print version: Loading...
  Rate this result: What is this?
  
  Please help us test our new pre-print finding feature by giving the pre-print link a rating.
  A 5 star rating indicates the linked pre-print has the exact same content as the published article.
  
  Abstract: Abstract In this paper, flexible preventive maintenance (PM) activities are incorporated into two-stage assembly flow shop scheduling where m dedicated machines in the fabrication stage and one machine in the assembly stage. The operational status of each machine is described by a continuous variable, maintenance level. The maintenance level value is inversely proportional to the processing time. Once a PM activity is performed, this value will return to the initial value. Different from the PM at fixed predefined time intervals, flexible PM can be carried out at any time point, but the maintenance levels are not less than 0. Hence, a MILP model with maintenance level constraints is formulated to minimize the total completion time and maintenance time. Regarding the methods, a latest PM decision strategy is proposed to determine the execution time of PM activities. This new strategy is embedded into 15 constructive heuristics and 7 meta-heuristics (three variants of iterated local search, three variants of Q-learning-based ant colony system with local search and a Q-learning-based hyper-heuristics) to address this new problem. The final experimental analysis demonstrates the significance of the integrated model and the effectiveness of the proposed constructive heuristics and meta-heuristics.
  PubDate: 2022-03-01
  DOI: 10.1007/s10696-021-09403-0
A dynamic prioritization policy for the callback option in a call center
- Free pre-print version: Loading...
  Rate this result: What is this?
  
  Please help us test our new pre-print finding feature by giving the pre-print link a rating.
  A 5 star rating indicates the linked pre-print has the exact same content as the published article.
  
  Abstract: Abstract In this paper, we study the $M_n/M_n/c/(K_1+K_2)+M_n$ system with two finite-size queues where underlying exponential random variables have state-dependent rates. When all servers are busy, upon arrival customers may join the online or the offline/callback queue or simply balk. Customers waiting in the online queue are impatient and if their patience expires, they may choose to join the callback queue instead of abandoning the system for good. Customers in the callback queue are assumed to be patient. Customers are served following a threshold policy: when the number of customers in the callback queue surpasses a threshold level, the next customer to serve is picked from here. Otherwise, only after a predetermined number of agents are reserved for future arrivals, customers remaining in the callback queue can be served. We conduct an exact analysis of this system and obtain its steady-state performance measures. The times spent in both queues are expressed as Phase-type distributions. With numerical examples, we present how the policy responds when shorter callback times are promised or customer characteristics vary.
  PubDate: 2022-03-01
  DOI: 10.1007/s10696-021-09413-y
Cost optimization in the $$(S-1, S)$$ ( S - 1 , S ) backorder inventory
model with two demand classes and rationing
- Free pre-print version: Loading...
  Rate this result: What is this?
  
  Please help us test our new pre-print finding feature by giving the pre-print link a rating.
  A 5 star rating indicates the linked pre-print has the exact same content as the published article.
  
  Abstract: Abstract Within the framework of continuous-review $(S-1, S)$ inventory systems with rationing and backorders, there are two streams of studies in the literature that involve optimization models. In the first stream, service level optimizations are studied for which exact optimization routines are provided. The second stream of studies involves cost optimization models, which relies on optimizing approximate cost models rather than the original cost model. Our main contribution in this study is to fill this research gap by providing a computationally efficient and exact optimization algorithm for determining the optimal policy parameters which minimizes the expected cost rate per unit time. One important aspect of our method is that, as the base-stock level is increased by 1 as the iteration continues, the steady-state probabilities need to be calculated only once in our optimization routine (for which the rationing level equals to zero). For the given base-stock level, the cost measures of all other policy parameters can be computed immediately through the knowledge of the probabilities computed in previous iterations. This result significantly reduces the computational complexity of the optimization routine. In the numerical study section, we show the efficiency of the proposed optimization routine under varying system parameters. We also compare the performance of our approach with the existing heuristic in the literature and show that savings up to $34.75 \%$ can be achieved.
  PubDate: 2022-03-01
  DOI: 10.1007/s10696-021-09418-7
Integrating Corporate Social Responsibility in a closed-loop supply chain
under government subsidy and used products collection strategies
- Free pre-print version: Loading...
  Rate this result: What is this?
  
  Please help us test our new pre-print finding feature by giving the pre-print link a rating.
  A 5 star rating indicates the linked pre-print has the exact same content as the published article.
  
  Abstract: Abstract Due to rapid advancement of the society, recently many manufacturing and retailing companies are showing their interests in Corporate Social Responsibility (CSR) in addition to maximizing their profits. This study introduces CSR activity of the retailer, and develops an integrated model (Model I) and three manufacturer-led decentralized models (Model M, R, and C) depending on different collection options of used products under selling price and CSR effort dependent market demand. The aim of this study is to explore how CSR effort of the retailer can influence the optimal decisions of the supply chain members. In order to stimulate the CSR effort, the government provides CSR dependent subsidy to the retailer. Besides deriving closed-form optimal solutions, this research also determines optimal consumer surplus, environmental damage and social welfare for the proposed models. A comparative study is performed to determine the best sustainable decentralized model. The numerical results show that among the three decentralized models, Model M gives the best performance but fails to challenge with Model I, and government subsidy plays a key role in improving channel performance. A two-part tariff contract is considered to address channel coordination issue. The effects of some key model-parameters on the optimal profitability and the social welfare are investigated through sensitivity analysis, which can help managers to implement CSR activity as well as improve channel performance.
  PubDate: 2022-03-01
  DOI: 10.1007/s10696-021-09404-z
Optimal pricing with free gift cards in a two-product supply chain
- Free pre-print version: Loading...
  Rate this result: What is this?
  
  Please help us test our new pre-print finding feature by giving the pre-print link a rating.
  A 5 star rating indicates the linked pre-print has the exact same content as the published article.
  
  Abstract: Abstract We develop a model of free gift card promotions in a two-product supply chain. We analyze three cases with different gift card strategies based on whether the wholesale and retail prices are changed or unchanged. The results indicate that, in the strategy of unchanged wholesale and retail prices, the retailer and two manufacturers are better off. The gift card promotions can effectively stimulate the demands of two products. We find that the two manufacturers benefit more from the gift card promotion than the retailer does. In the strategy of unchanged wholesale prices and changed retail prices, if the gift card value is not very large, the retailer’s profit margins and average consumer surplus from the gift card promotion are increasing in the gift card value. In the strategy of changed wholesale and retail prices, the retailer and two manufacturers have an incentive to raise the retail and wholesale prices under certain conditions. Furthermore, we show that, keeping the prices at the level of no gift cards is the dominant strategy for the supply chain and consumers, and the difference between retail prices and wholesale prices of two products is the key factor in determining the gift card value.
  PubDate: 2022-03-01
  DOI: 10.1007/s10696-021-09409-8