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 Subjects -> PHYSICS (Total: 800 journals)     - ELECTRICITY AND MAGNETISM (9 journals)    - MECHANICS (21 journals)    - NUCLEAR PHYSICS (51 journals)    - OPTICS (86 journals)    - PHYSICS (576 journals)    - SOUND (25 journals)    - THERMODYNAMICS (32 journals) PHYSICS (576 journals)            First | 1 2 3 | Last
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 Flexible Services and Manufacturing Journal   [SJR: 1.325]   [H-I: 34]   [1 followers]  Follow         Hybrid journal (It can contain Open Access articles)    ISSN (Print) 1936-6582 - ISSN (Online) 1936-6590    Published by Springer-Verlag  [2352 journals]
• Improved critical chain buffer management framework considering resource
costs and schedule stability
• Authors: Xuejun Hu; Erik Demeulemeester; Nanfang Cui; Jianjiang Wang; Wendi Tian
Pages: 159 - 183
Abstract: Abstract The critical chain scheduling and buffer management (CC/BM) methodology has proven to be a favorable approach to schedule resource-constrained projects and to offer a valuable control tool for monitoring projects under uncertainty. The previous studies on CC/BM seem to have neglected the cost performance, which might render its wider applications to the modern economic activities that are mostly performed in a project way. This paper presents an improved CC/BM framework that allows additional resource allocation/reallocation to bring forward activity starting times based on cost and schedule stability criteria. In the planning phase, the decision is made concerning the regular resource availability period in order to minimize the expected resource costs. In the execution phase, a scheduled order repair method for rescheduling along with two reactive resource allocation procedures as the corrective action whenever delays are beyond a certain buffer threshold are presented and examined in order to exhibit a comprehensive project schedule/cost control system that is adaptive to the CC/BM management logic. Finally, our computational experiment demonstrates the benefits of the proposed reactive methods under different cost or availability parameters.
PubDate: 2017-06-01
DOI: 10.1007/s10696-016-9241-y
Issue No: Vol. 29, No. 2 (2017)

• Solving integrated production and condition-based maintenance planning
problems by MIP modeling
• Authors: Fahimeh Shamsaei; Mathieu Van Vyve
Pages: 184 - 202
Abstract: Abstract It has been demonstrated that integrating maintenance scheduling and production planning can lead to substantial savings. However in these works the associated optimization problems are solved by enumerating all (exponentially many) maintenance schedules. This has led these researchers to either solve instances of very small sizes, or consider cyclic maintenance schedules only to limit the possibilities to a small (polynomial) number. We show here how to formulate these problems as (strong) mixed-integer linear programs, and then solve them using off-the-shelve MIP solvers. We demonstrate the efficiency of the proposed approach to solve problems of up to 10 products and 24 time periods, sizes that were simply unreachable before. We also illustrate the value of using non-cyclic maintenance schedules when the demand varies over time, with savings of up to 41 % compared to cyclic schedules.
PubDate: 2017-06-01
DOI: 10.1007/s10696-016-9244-8
Issue No: Vol. 29, No. 2 (2017)

• Shift scheduling with break windows, ideal break periods, and ideal
waiting times
• Authors: Banu Sungur; Cemal Özgüven; Yasemin Kariper
Pages: 203 - 222
Abstract: Abstract This paper is concerned with the shift scheduling problem involving multiple breaks with different durations and multiple break windows for each shift. We have incorporated ideal break periods and ideal waiting time into the original problem previously presented in the literature. As an extension of the implicit integer programming model with a single goal of minimizing the labor cost, we have proposed an implicit preemptive goal programming model involving three goals, which are given in order of their priority levels as follows: (1) minimize the labor cost; (2) maximize the number of employees that receive their breaks at ideal break periods; (3) make the waiting times of the employees between their consecutive breaks equal to the ideal waiting time, i.e. minimize the deviations from ideal waiting time. The ideal waiting time is incorporated into the model implicitly by matching the periods within the break windows. We aim at improving the break schedules through a more sensitive timing of the breaks, without causing an increase in the labor cost. The computational results obtained on randomly generated test problems indicate that the extended model may yield considerable improvement in the break placement.
PubDate: 2017-06-01
DOI: 10.1007/s10696-015-9234-2
Issue No: Vol. 29, No. 2 (2017)

• Solving the pre-marshalling problem to optimality with A* and IDA*
• Authors: Kevin Tierney; Dario Pacino; Stefan Voß
Pages: 223 - 259
Abstract: Abstract We present a novel solution approach to the container pre-marshalling problem using the A* and IDA* algorithms combined with several novel branching and symmetry breaking rules that significantly increases the number of pre-marshalling instances that can be solved to optimality. A* and IDA* are graph search algorithms that use heuristics combined with a complete graph search to find optimal solutions to problems. The container pre-marshalling problem is a key problem for container terminals seeking to reduce delays of inter-modal container transports. The goal of the container pre-marshalling problem is to find the minimal sequence of container movements to shuffle containers in a set of stacks such that the resulting stacks are arranged according to the time each container must leave the stacks. We evaluate our approach on three well-known datasets of pre-marshalling problem instances, solving over 500 previously unsolved instances to optimality, which is nearly twice as many instances as the current state-of-the-art method solves.
PubDate: 2017-06-01
DOI: 10.1007/s10696-016-9246-6
Issue No: Vol. 29, No. 2 (2017)

• Enhancement of supply chain resilience through inter-echelon information
sharing
• Authors: Haobin Li; Giulia Pedrielli; Loo Hay Lee; Ek Peng Chew
Pages: 260 - 285
Abstract: Abstract Supply chains in the globally interconnected society have complex structures and thus are susceptible to disruptions such as natural disasters and diseases. The impact of the risks and disruptions that occur to one business entity can propagate to the entire supply chain. However, it has been proposed that cooperation amongst business entities can mitigate the impact of the risks. This paper aims to investigate the value of information sharing in a generalized three-echelon supply chain. The supply chain model is built in a system dynamics software, and three decision-making rules based on different levels of information sharing are developed. Performances of the three ordering policies with shock applied are compared. The results of the experiments prove the value of information sharing in the supply chain when shock exists.
PubDate: 2017-06-01
DOI: 10.1007/s10696-016-9249-3
Issue No: Vol. 29, No. 2 (2017)

• Flexibility design in loss and queueing systems: efficiency of k -chain
configuration
• Authors: Jingui Xie; Yiming Fan; Mabel C. Chou
Pages: 286 - 308
Abstract: Abstract Process flexibility has altered operations in manufacturing and service companies significantly. For instance, auto-mobile manufacturers use flexible production systems to meet uncertain demands effectively, and workforce flexible systems with cross-training are presently common in service industries. This paper studies k-chain configuration in both loss systems and queueing systems. We derive performance measures such as percent of customers loss and average customer waiting time. In the symmetric case, we numerically test the effects of k , system size and traffic intensity on flexibility design. The major conclusion is that 2-chain is no longer effective in loss systems although it still performs well in queueing systems.
PubDate: 2017-06-01
DOI: 10.1007/s10696-016-9251-9
Issue No: Vol. 29, No. 2 (2017)

• Finding the trade-off between emissions and disturbance in an urban
context
• Authors: Jasmin Grabenschweiger; Fabien Tricoire; Karl F. Doerner
Abstract: Abstract We introduce the bi-objective emissions disturbance traveling salesman problem (BEDTSP), which aims at minimizing carbon dioxide emissions ( $$\hbox {CO}_2$$ ) as well as disturbance to urban neighborhoods, when planning the tour of a single vehicle delivering goods to customers. Although there exist recent studies on minimizing emissions, we are not aware of any work on minimizing disturbance. We develop four different mathematical models for the BEDTSP. We also develop several data generation strategies for minimizing disturbance. These strategies consider optional nodes, thus allowing detours that yield less disturbance but also possibly more emissions. All models and strategies are compared in an extensive computational study. Experimental results allow us to derive clear guidelines for which model and data generation strategy to use in which context. Following these guidelines, we conduct a case study for the city of Vienna.
PubDate: 2017-10-14
DOI: 10.1007/s10696-017-9297-3

• Simulated annealing with different vessel assignment strategies for the
continuous berth allocation problem
• Authors: Shih-Wei Lin; Ching-Jung Ting; Kun-Chih Wu
Abstract: Abstract The berth allocation problem is an optimization problem concerning seaside operations at container terminals. This study investigates the dynamic and continuous berth allocation problem (BAP), whose objective is to minimize the total weighted service time and the deviation cost from vessels’ preferred position. The problem is formulated as a mixed integer programming model. Due to that the BAP is NP-hard, two efficient and effective simulated annealing (SA) algorithms are proposed to locate vessels along the quay. The first SA assigns vessels to available positions along the quay from the left to the right, while the second assigns vessels from both sides. Both small and large-scale instances in the literature are tested to evaluate the effectiveness of the proposed SA algorithms using the optimization software Gurobi and heuristic algorithms from the literature. The results indicate that the proposed SAs can provide optimal solutions in small-scale instances and updates the best solutions in large-scale instances. The improvement over other comparing heuristics is statistically significant.
PubDate: 2017-10-14
DOI: 10.1007/s10696-017-9298-2

• Analysis, design, and management of health care systems
• Authors: Andrea Matta; Alain Guinet; Jingshan Li; Evren Sahin; Nico Vandaele
PubDate: 2017-09-20
DOI: 10.1007/s10696-017-9294-6

• Sailing speed optimization for tramp ships with fuzzy time window
• Abstract: Abstract This paper studies the problem of the sailing speed optimization for tramp ships. The transportation time requirements which are associated with shippers’ satisfaction are considered by a fuzzy membership function. A bi-objective model is proposed in which the minimum operation cost and the maximum shippers’ satisfaction are optimized simultaneously. The optimal speed on each leg of a given ship route is determined. A fast elitist non-dominated sorting genetic algorithm (NSGAII) is improved to solve the problem. To test the performance of the proposed model and algorithm, a numerical experiment is designed. The results show that the proposed algorithm has good convergence property and convergence speed.
PubDate: 2017-09-09
DOI: 10.1007/s10696-017-9296-4

• Two decision models for berth allocation problem under uncertainty
considering service level
• Abstract: Abstract This paper examines the berth allocation problem, which is to assign a quay space and a service time to the vessels that have to be loaded and unloaded at a container terminal within a given planning horizon, with consideration of uncertain factors, mainly including the arrival and operation time of the calling vessels. Based on the concept of conflict, two kinds of service level are proposed and two decision models are constructed to minimize the total operational cost, which includes delay cost and non-optimal berthing location cost. The first model satisfies the service level of a specific scenario and the second one considers the service level across all scenarios. Due to the NP-hardness of the constructed model, a two-stage heuristics algorithm is employed to solve the problem. Finally, extensive numerical experiments are conducted to test the performances of the two proposed models and algorithm and help the port planners make decisions.
PubDate: 2017-09-08
DOI: 10.1007/s10696-017-9295-5

• Editorial of special issue on ocean transportation logistics: making
global supply chain effective
• Authors: Kjetil Fagerholt; Kap-Hwan Kim; Chung-Yee Lee; Qiang Meng; Xiangtong Qi
PubDate: 2017-08-30
DOI: 10.1007/s10696-017-9293-7

• Railway capacity and expansion analysis using time discretized paths
• Authors: Line Blander Reinhardt; David Pisinger; Richard Lusby
Abstract: Abstract When making investments in railway infrastructure it is important to be able to identify the limits for freight transportation in order to not only use the infrastructure in the best possible way, but to also guide future capacity investments. This paper presents a model to assess the capacity of railway freight transportation on a long term strategic level. The model uses an hourly time discretization and analyses the impact of railway network expansions based on future demand forecasts. It provides an optimal macroscopic freight train schedule and can indicate the time and place of any congestion. In addition, two expansions of the primary model are developed. The first can be used to determine the minimal number of expansions needed to ensure all freight can be feasibly routed, while the second can be used to schedule freight trains at hours not congested by passenger trains using variable penalties for the different passenger busy time slots. As part of a European Union project, all models are applied to a realistic case study that focuses on analyzing the capacity of railway network, in Denmark and Southern Sweden using demand forecasts for 2030. Results suggest that informative solutions can be found quickly with the proposed approach.
PubDate: 2017-08-16
DOI: 10.1007/s10696-017-9292-8

• A stochastic online algorithm for unloading boxes from a conveyor line
• Authors: Reinhard Bürgy; Pierre Baptiste; Alain Hertz; Djamal Rebaine; André Linhares
Abstract: Abstract This article discusses the problem of unloading a sequence of boxes from a single conveyor line with a minimum number of moves. The problem under study is efficiently solvable with dynamic programming if the complete sequence of boxes is known in advance. In practice, however, the problem typically occurs in a real-time setting where the boxes are simultaneously placed on and picked from the conveyor line. Moreover, a large part of the sequence is often not visible. As a result, only a part of the sequence is known when deciding which boxes to move next. We develop an online algorithm that evaluates the quality of each possible move with a scenario-based stochastic method. Two versions of the algorithm are analyzed: in one version, the quality of each scenario is measured with an exact method, while a heuristic technique is applied in the second version. We evaluate the performance of the proposed algorithms using extensive computational experiments and establish a simple policy for determining which version to choose for specific problems. Numerical results show that the proposed approach consistently provides high-quality results, and compares favorably with the best known deterministic online algorithms. Indeed, the new approach typically provides results with relative gaps of 1–5% to the optimum, which is about 20–80% lower than those obtained with the best deterministic approach.
PubDate: 2017-07-12
DOI: 10.1007/s10696-017-9291-9

• Delivery mode planning for distribution to brick-and-mortar retail stores:
discussion and literature review
• Authors: Sara Martins; Pedro Amorim; Bernardo Almada-Lobo
Abstract: Abstract In the retail industry, there are multiple products flowing from different distribution centers to brick-and-mortar stores with distinct characteristics. This industry has been suffering radical changes along the years and new market dynamics are making distribution more and more challenging. Consequently, there is a pressure to reduce shipment sizes and increase the delivery frequency. In such a context, defining the most efficient way to supply each store is a critical task. However, the supply chain planning decision that tackles this type of problem, delivery mode planning, is not well defined in the literature. This paper proposes a definition for delivery mode planning and analyzes multiple ways retailers can efficiently supply their brick-and-mortar stores from their distribution centers. The literature addressing this planning problem is reviewed and the main interdependencies with other supply chain planning decisions are discussed.
PubDate: 2017-05-15
DOI: 10.1007/s10696-017-9290-x

• A solution approach for deriving alternative fuel station infrastructure
requirements
• Authors: Roel M. Post; Paul Buijs; Michiel A. J. uit het Broek; Jose A. Lopez Alvarez; Nick B. Szirbik; Iris F. A. Vis
Abstract: Abstract When an alternative fuel is introduced, the infrastructure through which that fuel is made available to the market is often underdeveloped. Transportation service providers relying on such infrastructures are unlikely to adopt alternative fuel vehicles as it may impose long detours for refueling. In this paper, we design and apply a new solution approach to derive minimum infrastructure requirements, in terms of the number of alternative fuel stations. The effectiveness of our approach is demonstrated by applying it to the case of introducing liquefied natural gas (LNG) as a transportation fuel in The Netherlands. From this case, we learn that, depending on the driving range of the LNG trucks and the size of area on which those trucks operate, a minimum of 5–12 LNG fuel stations is necessary to render LNG trucks economically and environmentally beneficial.
PubDate: 2017-04-21
DOI: 10.1007/s10696-017-9289-3

• Sustainable sourcing of strategic raw materials by integrating recycled
materials
• Authors: Patricia Rogetzer; Lena Silbermayr; Werner Jammernegg
Abstract: Abstract In this paper we investigate a manufacturer’s sustainable sourcing strategy that includes recycled materials. To produce a short life-cycle electronic good, strategic raw materials can be bought from virgin material suppliers in advance of the season and via emergency shipments, as well as from a recycler. Hence, we take into account virgin and recycled materials from different sources simultaneously. Recycling makes it possible to integrate raw materials out of steadily increasing waste streams back into production processes. Considering stochastic prices for recycled materials, stochastic supply quantities from the recycler and stochastic demand as well as their potential dependencies, we develop a single-period inventory model to derive the order quantities for virgin and recycled raw materials to determine the related costs and to evaluate the effectiveness of the sourcing strategy. We provide managerial insights into the benefits of such a green sourcing approach with recycling and compare this strategy to standard sourcing without recycling. We conduct a full factorial design and a detailed numerical sensitivity analysis on the key input parameters to evaluate the cost savings potential. Furthermore, we consider the effects of correlations between the stochastic parameters. Green sourcing is especially beneficial in terms of cost savings for high demand variability, high prices of virgin raw material and low expected recycling prices as well as for increasing standard deviation of the recycling price. Besides these advantages it also contributes to environmental sustainability as, compared to sourcing without recycling, it reduces the total quantity ordered and, hence, emissions are reduced.
PubDate: 2017-04-05
DOI: 10.1007/s10696-017-9288-4

• Integration of order picking and vehicle routing in a B2C e-commerce
context
• Authors: Stef Moons; Katrien Ramaekers; An Caris; Yasemin Arda
Abstract: Abstract E-commerce sales are increasing every year and customers who buy goods on the Internet have high service level expectations. In order to meet these expectations, a company’s logistics operations need to be performed carefully. Optimizing only internal warehouse processes will often lead to suboptimal solutions. The interrelationship between the order picking process and the delivery process should not be ignored. Therefore, in this study, an order picking problem and a vehicle routing problem with time windows and release dates are solved simultaneously using a single optimization framework. To the best of our knowledge, it is the first time that an order picking problem and a vehicle routing problem are integrated. A mixed integer linear programming formulation for this integrated order picking-vehicle routing problem (OP-VRP) is provided. The integrated OP-VRP is solved for small instances and the results are compared to these of an uncoordinated approach. Computational experiments show that integration can lead to cost savings of 14% on average. Furthermore, higher service levels can be offered by allowing customers to request their orders later and still get delivered within the same time windows.
PubDate: 2017-03-31
DOI: 10.1007/s10696-017-9287-5

• A stochastic approach for designing two-tiered emergency medical service
systems
• Authors: Rania Boujemaa; Aida Jebali; Sondes Hammami; Angel Ruiz; Hanen Bouchriha
Abstract: Abstract Emergency medical services (EMS) systems provide out-of-hospital acute medical care and transportation to the appropriate health care provider to patients with illnesses and injuries. The objective of EMS systems is to satisfy demand requests by providing timely first care medical assistance to patients at the incident scene. This paper aims at designing a robust two-tiered EMS system while accounting for the inherent uncertainty of the demand. A two-stage stochastic programming location-allocation model is proposed to simultaneously determine the location of ambulance stations, the number and the type of ambulances to be deployed, and the demand areas served by each station. This problem is then solved efficiently using the sampling average approximation algorithm. Computational experiments highlight the performance of the proposed solution approach and its practical applicability.
PubDate: 2017-03-22
DOI: 10.1007/s10696-017-9286-6

• Cooperative liner shipping network design by means of a combinatorial
auction
• Authors: Tobias Buer; Rasmus Haass
Abstract: Abstract Cooperation in the ocean liner shipping industry has always been important to improve liner shipping networks (LSN’s). As tight cooperations like alliances are challenged by antitrust laws, looser forms of cooperation among liner carriers might become a reasonable way to increase efficiency of LSN’s. Our goal is to facilitate a loose form of cooperation among liner carriers. Therefore, we introduce a coordination mechanism for designing a collaborative LSN based on a multi round combinatorial auction. Via the auction, carriers exchange demand triplets, i.e. orders which describe the transport of containers between ports. A standard network design problem which includes ship scheduling and cargo routing decisions is used as isolated network design problem of an individual carrier. A carrier has to solve this isolated problem repeatedly during the auction so that the carrier is able to decide which demand triplets to sell, on which demand triplets to bid, and what prices to charge. To solve these problems we propose a variable neighborhood search based matheuristic. The matheuristic addresses the isolated planning problem in four phases (construct ship cycles, modify cycles, determine container flow, and reallocate ships to cycles). Our computational experiments on a set of 56 synthetic test instances suggest that the introduced combinatorial auction increases profits on average compared to isolated planning significantly by 4%. The more diverse the original assignment of demand triplets and ships to carriers is, the higher the potential for collaboration; for 18 diverse instances, the profits increase on average by 10%.
PubDate: 2017-03-18
DOI: 10.1007/s10696-017-9284-8

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