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1 – 10 of over 99000Christopher Rose and Jenny Coenen
The purpose of this paper is to present a method for generating a set of feasible, optimized production schedules for the erection process of compact shipyards building complex…
Abstract
Purpose
The purpose of this paper is to present a method for generating a set of feasible, optimized production schedules for the erection process of compact shipyards building complex ship types.
Design/methodology/approach
A bi-objective mathematical model is developed based on the process constraints. A Pareto front of possible erection schedules is created using a the Non-dominated Sorting Genetic Algorithm II with a custom heuristic fitness function and constraint violation.
Findings
It was possible to consistently generate a wide variety of production schedules with superior performance to those manually created by shipyard planner in negligible computational time.
Practical implications
The set of optimized production schedules generated by the developed methodology can be used as a starting point by existing shipyard planners when drafting the initial erection planning for a new project. This allows the planners to consider wider variety of options in less time.
Originality/value
No other published approach for the automatic generation of optimized production schedules of the erection process is specifically tailored to the construction of complex ships.
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Alexandros Kallantzis and Sergios Lambropoulos
A scheduling method for determining the critical path in linear projects is presented, that takes into account maximum time and distance constraints in addition to the commonly…
Abstract
A scheduling method for determining the critical path in linear projects is presented, that takes into account maximum time and distance constraints in addition to the commonly used minimum time and distance constraints. The maximum constraints, though often present in the specifications of a project, are not considered during the planning procedure, since no method existed to enable scheduling with them. The proposed method builds on the concept of the maximum constraints and expands on the necessary background for their implementation into the schedule. The introduced critical path algorithm allows for grouping linear activities into four categories regarding their critical status and their ability to influence project duration. The method is applied to a low‐pressure pipeline construction project and the results are presented.
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Jun Wen, Metin Kozak and Tianyu Ying
Given the increasing number of tourists exposed to commercially available cannabis, it is important to understand visitors' perceived constraints to cannabis consumption while…
Abstract
Purpose
Given the increasing number of tourists exposed to commercially available cannabis, it is important to understand visitors' perceived constraints to cannabis consumption while travelling. This study aims to compare cannabis tourists' perceived constraints between first-time and repeat tourists to gain comprehensive understanding.
Design/methodology/approach
This study involved 32 conversational field interviews (5–10 min) with Chinese tourists who had smoked cannabis in coffee shops in Amsterdam to identify perceived constraints to engaging in cannabis tourism. The hierarchical constraint model (HCM) informed qualitative data coding using a deductive approach to compare first-time and repeat tourists. Content analysis was conducted manually.
Findings
Results showed that both tourist groups faced intrapersonal, interpersonal and structural perceived constraints to cannabis consumption. Differences in first-time and repeat cannabis tourists' perceived constraints were explained using the neutralization technique framework and psychological tactics, such as the defence of necessity, claims of entitlement, normal practice and claims of relative acceptability. In addition, social exchange theory was employed to explain why repeat cannabis tourists perceived fewer constraints than first-time tourists.
Practical implications
Although the current study did not intend to address the importance of cannabis tourism in places where cannabis is commercially available, findings offer empirical guidance for industry practitioners and policymakers regarding cannabis use education, prevention and policy in tourism contexts; related efforts can promote the sustainable development of this tourism market while protecting cannabis tourists' physical and psychological well-being.
Originality/value
This study makes important theoretical contributions regarding travel constraints in the unique context of cannabis tourism between first-time and repeat tourists. Findings will also enable academics, industry operators, policymakers and local residents of cannabis tourism destinations to better understand how these tourists decide whether to consume cannabis overseas. Differences in these perceived constraints between first-time and repeat tourists are discussed to highlight the dynamic nature of travel constraints.
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The purpose of this paper is cost optimization of project schedules under constrained resources and alternative production processes (APPs).
Abstract
Purpose
The purpose of this paper is cost optimization of project schedules under constrained resources and alternative production processes (APPs).
Design/methodology/approach
The model contains a cost objective function, generalized precedence relationship constraints, activity duration and start time constraints, lag/lead time constraints, execution mode (EM) constraints, project duration constraints, working time unit assignment constraints and resource constraints. The mixed-integer nonlinear programming (MINLP) superstructure of discrete solutions covers time–cost–resource options related to various EMs for project activities as well as variants for production process implementation.
Findings
The proposed model provides the exact optimal output data for project management, such as network diagrams, Gantt charts, histograms and S-curves. In contrast to classic scheduling approaches, here the optimal project structure is obtained as a model-endogenous decision. The project planner is thus enabled to achieve optimization of the production process simultaneously with resource-constrained scheduling of activities in discrete time units and at a minimum total cost.
Practical implications
A set of application examples are addressed on an actual construction project to display the advantages of proposed model.
Originality/value
The unique value this paper contributes to the body of knowledge reflects through the proposed MINLP model, which is capable of performing the exact cost optimization of production process (where presence and number of activities including their mutual relations are dealt as feasible alternatives, meaning not as fixed parameters) simultaneously with the associated resource-constrained project scheduling, whereby that is achieved within a uniform procedure.
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Buffers of work throughout a manufacturing facility enhance throughput. They protect a workstation against variations in processing times and against machine breakdowns of…
Abstract
Buffers of work throughout a manufacturing facility enhance throughput. They protect a workstation against variations in processing times and against machine breakdowns of upstream workstations. However, buffer management is still thought to be an open problem: first there is no algebraic way of representing the relationship between buffer size and throughput, and second, the combinatorial nature inherent in the buffer design problem makes it difficult to develop an exact solution. These problems still exist today, as evidenced by the number of research papers that present sophisticated mathematics to solve this complex problem. Refutes all the above points. The buffer management method detailed does not use sophisticated mathematics impenetrable by the average production manager. Presents a heuristically‐based buffer management method effective at protecting throughput. The method will have advantageous effects on the size of buffers and the length of the production lead times, while still providing protection of the throughput rate.
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Muhaned Gilani and Durmuş Sinan Körpe
This paper aims to minimize aircraft fuel consumption during the cruise phase when the flight is subjected to a specific time of arrival for different weights and distances.
Abstract
Purpose
This paper aims to minimize aircraft fuel consumption during the cruise phase when the flight is subjected to a specific time of arrival for different weights and distances.
Design/methodology/approach
The approach adopted herein uses sequential quadratic programming algorithm from MATLAB optimization toolbox, which includes a mathematical model of a jet airliner based on the Base of Aircraft Data as a function evaluator, to find out the impact of meet-time of arrival constraints on fuel consumption. The cruising speeds at predefined segments and the altitude are defined as the design variables.
Findings
The algorithm determines the optimum cruise altitudes and speeds for minimum fuel consumption in the case of no time constraints, also, for different time constraints where the flight time shall be reduced by increasing speed and lowering the altitude in most of the investigated cases.
Practical implications
The algorithm computes the optimum speed and the altitude according to different flight scenarios with the meet-time of arrival constraints for minimum fuel consumption which affects the direct operating cost of the flight. The algorithm might greatly help in decision-making for the meet-time of arrival operations.
Originality/value
Developing an algorithm to optimize the speed and the altitude of an aircraft based on weight and range for minimization of fuel consumption. It is a pioneer study in the literature that deals with the effect of meet-time constraints on fuel consumption.
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Mohammad Yaghtin and Youness Javid
The purpose of this research is to address the complex multiobjective unrelated parallel machine scheduling problem with real-world constraints, including sequence-dependent setup…
Abstract
Purpose
The purpose of this research is to address the complex multiobjective unrelated parallel machine scheduling problem with real-world constraints, including sequence-dependent setup times and periodic machine maintenance. The primary goal is to minimize total tardiness, earliness and total completion times simultaneously. This study aims to provide effective solution methods, including a Mixed-Integer Programming (MIP) model, an Epsilon-constraint method and the Nondominated Sorting Genetic Algorithm (NSGA-II), to offer valuable insights into solving large-sized instances of this challenging problem.
Design/methodology/approach
This study addresses a multiobjective unrelated parallel machine scheduling problem with sequence-dependent setup times and periodic machine maintenance activities. An MIP model is introduced to formulate the problem, and an Epsilon-constraint method is applied for a solution. To handle the NP-hard nature of the problem for larger instances, an NSGA-II is developed. The research involves the creation of 45 problem instances for computational experiments, which evaluate the performance of the algorithms in terms of proposed measures.
Findings
The research findings demonstrate the effectiveness of the proposed solution approaches for the multiobjective unrelated parallel machine scheduling problem. Computational experiments on 45 generated problem instances reveal that the NSGA-II algorithm outperforms the Epsilon-constraint method, particularly for larger instances. The algorithms successfully minimize total tardiness, earliness and total completion times, showcasing their practical applicability and efficiency in handling real-world scheduling scenarios.
Originality/value
This study contributes original value by addressing a complex multiobjective unrelated parallel machine scheduling problem with real-world constraints, including sequence-dependent setup times and periodic machine maintenance activities. The introduction of an MIP model, the application of the Epsilon-constraint method and the development of the NSGA-II algorithm offer innovative approaches to solving this NP-hard problem. The research provides valuable insights into efficient scheduling methods applicable in various industries, enhancing decision-making processes and operational efficiency.
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Peng Peng and Zhigang Xu
Large-scale farm management in China has developed rapidly in recent years. Large-scale farmers face substantial operating risks, requiring extensive price risk management…
Abstract
Purpose
Large-scale farm management in China has developed rapidly in recent years. Large-scale farmers face substantial operating risks, requiring extensive price risk management. However, the agricultural insurance and futures markets in China are incomplete. This study aims to analyze the price-risk-management behaviors of large-scale farmers under incomplete market conditions, with a focus on the interconnections between large scale farmers' subjective preferences (risk preferences, time preferences), liquidity constraints and their price risk management.
Design/methodology/approach
The authors construct an analysis framework to reveal the impact of large-scale farmers' risk preferences, time preferences and liquidity conditions on their price-risk-management behaviors under incomplete market conditions. Using data from field surveys and subjective preference experiments involving 409 large-scale grain farmers in China, an empirical analysis was conducted using the bivariate probit model.
Findings
The results show that risk-averse farmers will use risk transfer (such as contract farming) and risk diversification (such as multi-period sales) to avoid price risk. However, farmers subject to liquidity constraints and strong time preferences will not choose risk diversification, and the interaction between time preferences and liquidity constraints will strengthen this decision. The larger the farm-management scale, the greater the impact.
Originality/value
The authors focus on rapidly developed large-scale farm management in China. Appropriate price risk management is required by large-scale farmers due to their substantial operating risks. Considering the incomplete conditions of agricultural insurance and futures markets, the results of this study will help identify behavioral characteristics of large-scale farmers and optimize their price-risk-management strategies, further stabilizing large-scale farm management.
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Jian Hu, Naigang Cui, Yuliang Bai and Yunhai Geng
The purpose of this paper is to present a novel guidance law that is able to control the impact time while the seeker’s field of view (FOV) is constrained.
Abstract
Purpose
The purpose of this paper is to present a novel guidance law that is able to control the impact time while the seeker’s field of view (FOV) is constrained.
Design/methodology/approach
The new guidance law is derived from the framework of Lyapunov stability theory to ensure interception at the desired impact time. A time-varying guidance gain scheme is proposed based on the analysis of the convergence time of impact time error, where finite-time stability theory is used. The circular trajectory assumption is adopted for the derivation of accurate analytical estimation of time-to-go. The seeker’s FOV constraint, along with missile acceleration constraint, is considered during guidance law design, and a switching strategy to satisfy it is designed.
Findings
The proposed guidance law can drive missile to intercept stationary target at the desired impact time, as well as satisfies seeker’s FOV and missile acceleration constraints during engagement. Simulation results show that the proposed guidance law could provide robustness against different engagement scenarios and autopilot lag.
Practical implications
The presented guidance law lays a foundation for using cooperative strategies, such as simultaneous attack.
Originality/value
This paper presents further study on the impact time control problem considering the seeker’s FOV constraint, which conforms better to reality.
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