This paper intends to address the distributed flexible job shop scheduling problem (DFJSP) with minimizing maximum completion time (makespan). In order to solve this problem, we propose four mixed integer linear progr...
详细信息
This paper intends to address the distributed flexible job shop scheduling problem (DFJSP) with minimizing maximum completion time (makespan). In order to solve this problem, we propose four mixed integer linear programming (MILP) models as well as a constraint programming (CP) model, among which four MILP models are formulated based on four different modeling ideas. MILP models are effective in solving small-scaled problems to optimality. DFJSP is NP-hard, therefore, we propose an efficient constraint programming (CP) model based on interval decision variables and domain filtering algorithms. Numerical experiments are conducted to evaluate the performance of the proposed MILP models and CP model. The results show that the sequence-based MILP model is the most efficient one, and the proposed CP model is effective in finding good quality solutions for the both the small-sized and large-sized instances. The CP model incomparably outperforms the state-of-the-art algorithms and obtains new best solutions for 11 benchmark problems. Moreover, the best MILP model and CP model have proved the optimality of 62 best-known solutions.
In this paper, an optimization model for optimal size and dispatch planning of micro combined heat and power systems regarding distinct structures for the inclusion of the cogeneration unit, auxiliary boiler, heat sto...
详细信息
In this paper, an optimization model for optimal size and dispatch planning of micro combined heat and power systems regarding distinct structures for the inclusion of the cogeneration unit, auxiliary boiler, heat storage and battery storage in the configuration of the system is introduced. The presented model is developed in a unified form by the implementation of constraint programming to consider different strategies for the system's operation. Furthermore, important details such as minimum/maximum permissible state of charge, maximum charge/ discharge rate and battery inverter for modeling practical storages as technical specifications and simultaneous consideration of calendar life and life cycle as service life as well as assessment of heat dumping avoidance has been taken into account in this study. The model has been applied to three operation strategies and four kinds of buildings while considering two single-objective and one multi-objective optimization for minimization of the greenhouse gas emissions and annual costs of the system. The study has been validated by multiple study cases and the analyzes indicate that the implementation of different structures for the configuration of the micro CHP systems can impressively affect the optimum size and dispatch of these systems in each operation strategy. Comparison of the obtained results for the candidate multi-criteria solutions considering the exploitation of different storage options indicates that the inclusion of the heat storage by up to 21.5% further reduction in annual expenditures with an equal amount of emissions is a more influential energy storage option for utilization in the proposed residential cogeneration system. Regarding heat dumping assumption, dumping avoidance can be a powerful key factor in the system's management to prevent extra greenhouse generations by restricting the heedless minimization of the annual costs when it adversely affects the generation of the emissions.
This study considers recycling the products to reuse or reproduce the precious parts of these products to provide environmental sustainability and for companies to adapt to competitive conditions. These recycling proc...
详细信息
This study considers recycling the products to reuse or reproduce the precious parts of these products to provide environmental sustainability and for companies to adapt to competitive conditions. These recycling processes include the dismantling of the products using the disassembly lines. Disassembly line balancing problems contribute to these processes by ensuring that products are disassembled efficiently and at minimum cost. Therefore, these problems have started to attract more attention in the literature. This study considers the disassembly line balancing problem, with sequence-dependent setup time and complex AND/OR precedence relations between tasks. The managerial impacts highlighted by the proposed problem are of great importance both from environmental and industrial sustainability due to the recycling process of the life-threatening wastes. The study aims to disassemble the products using a minimum number of workstations. Mixed-integer linear programming and constraint programming models have been developed for the considered problem in question. As far as is known, the sequence-dependent disassembly line balancing problem, which has complex precedence relations, has not been studied in the literature before, and the constraint programming model developed is also novel. The study also compares the constraint programming model with/without an initial solution. In addition, a simulated annealing metaheuristic is proposed to solve the problem, and its results are compared with the results of the models. Setup times were generated for well-known instances obtained from the literature. The results obtained using these instances showed that the constraint programming model successfully solved the problem under consideration
Decision-making in everyday life has an essential role in effectively completing personal tasks and processes. The complexity of these processes and the resulting cognitive load of managing them may vary significantly...
详细信息
Decision-making in everyday life has an essential role in effectively completing personal tasks and processes. The complexity of these processes and the resulting cognitive load of managing them may vary significantly. To decrease the cognitive load created by such decision-making efforts and to obtain better outcomes, recommendation systems carry significant potential. In order to investigate the benefits provided by decision support systems (DSS) in personal process management (PPM), we first build a constraint programming (CP) model and a prototype context-aware-mobile application employing this CP model. Then, we evaluate the application and the model via two exemplary real-world scenarios. The scenarios form the core of the experiments conducted with 50 participants. We compare the participants' planning performances with and without the PPM system with quantitative metrics such as planning times and scenario objective values. In addition, System Usability Scale (SUS) questionnaires and open-ended questions provide qualitative evaluation results. Throughout the study, we apply the Design Science Research methodology to rigorously conduct research activities by proof of concept, proof of use, and proof of value. The empirical results clearly show that our proposed model for PPM is effective, and the developed prototype solution generates positive participant comments as well as a high SUS score. Overall, the prototype PPM system with CP implementation leads to better planning in less time in the planning phase, and it lets the user do fast replanning in the execution phase, which is invaluable in dynamically changing situations such as daily activities.
It is increasingly recognized that automated decision making systems cannot be black boxes: users require insight into the reasons that decisions are made. Explainable AI (XAI) has developed a number of approaches to ...
详细信息
The multi-skill resource constrained project scheduling is an important and challenging problem in project management. Two key issues that turn this topic into a challenging problem are the assumptions that are consid...
详细信息
The multi-skill resource constrained project scheduling is an important and challenging problem in project management. Two key issues that turn this topic into a challenging problem are the assumptions that are considered to approximate the model to a real-world problem and exact solution approach for the model. In this paper, we deal with this two issues. To consider real-word situations, we take into account calendars specifying time intervals during which the resources are available. We proposed a constraint programming approach to solve the problem exactly. The problem with and without resource calendars are modeled with mathematical programming (MP) and constraint programming (CP). In addition, the performance of CP approach is evaluated by comparing Time-Indexed Model (TIM) and Branch and Price (B&P) approaches. Computational results show that the proposed approach can efficiently solve real-size instances.
In the container terminals of seaports, the container handling system consists of a variety of container handling machines such as quay cranes, internal yard trucks, and yard cranes. This study applies a holistic appr...
详细信息
In the container terminals of seaports, the container handling system consists of a variety of container handling machines such as quay cranes, internal yard trucks, and yard cranes. This study applies a holistic approach to the integrated scheduling of these machines for the container handling operations of a single vessel. We formulate this special hybrid flow shop scheduling problem through both mixed integer programming (MIP) and constraint programming (CP) techniques. Then we develop an easily-implemented approach that combines the strengths of MIP and CP. First, the MIP model, which only considers quay crane scheduling, is solved by an MIP solver, and a quay crane allocation plan is retrieved from the MIP solution. Then, this quay crane allocation plan is fed to the CP model, warm-starting the branch-and-prune algorithm built in a CP optimizer. Our numerical experiments reveal that this hybrid MIP/CP approach can solve the large-sized instances with up to 10 00 containers, 6 quay cranes, 36 yard trucks, and 15 yard cranes to optimality with a gap of less than 3.31%, within a solution time of 2 minutes. If we increase the solution time to 5 minutes, this hybrid approach solves larger instances with up to 1400 containers to optimality with a gap of less than 1.41%. The state-of-the-art dedicated algorithms reported in the literature (which address an easier version of the same problem by ignoring non-crossing constraints and safety margins between quay cranes) are only able to find solutions for real-life instances with up to 500 containers within the solution time of 2930 or 5221 seconds, leaving a 4% or an unknown optimality gap. Thus, this study improves the solution of this integrated scheduling problem in terms of the instance size, solution efficiency, and solution optimality. (C) 2020 Elsevier B.V. All rights reserved.
Bad construction of modeled care pathways can lead to satisfiability problems during the pathway execution. These problems can ultimately result in medical errors and need to be checked as formally as possible. Theref...
详细信息
Bad construction of modeled care pathways can lead to satisfiability problems during the pathway execution. These problems can ultimately result in medical errors and need to be checked as formally as possible. Therefore, this study proposes a set of algorithms using a free open-source library dedicated to constraint programming allied with a DSL to encode and verify care pathways, checking four possible problems: states in deadlock, non-determinism, inaccessible steps and transitions with logically equivalent guard conditions. We then test our algorithms in 84 real care pathways used both in hospitals and surgeries. Using our algorithms, we were able to find 200 problems taking less than 1 second to complete the verification on most pathways.
This paper presents the results of a research project aiming to optimise the scheduling of activities within a research laboratory of the 'Commissariat a l'Energie Atomique et aux Energies Alternatives (CEA)...
详细信息
This paper presents the results of a research project aiming to optimise the scheduling of activities within a research laboratory of the 'Commissariat a l'Energie Atomique et aux Energies Alternatives (CEA)'. To tackle this problem, we decompose every activity into a set of elementary tasks to apply standard scheduling methods. We model the problem as an extended version of the Multi-Skill Project Scheduling Problem (MSPSP). As a first approach, we propose a Multi-Skill Project Scheduling Problem with penalty for preemption, along with its mixed-integer/linear programming (MILP) formulation, where the preemption is allowed applying a penalty every time an activity is interrupted. However, the previous approach does not take into account all safety constraints at the facility, and a more accurate variant of the problem is needed. We propose then to integrate the concept of partial preemption to the MSPSP. This concept, that has not been yet studied in the scientific literature, implies that only a subset of resources is released during preemption periods. The resulting MSPSP with partial preemption (MSPSP-PP) is modelled using two methodologies: MILP and constraint programming. Regarding the industrial need of having good solutions in a short time, we also present a greedy algorithm for the MSPSP-PP.
The cyclic hoist scheduling problem (CHSP) is a well-studied optimisation problem due to its importance in industry. Despite the wide range of solving techniques applied to the CHSP and its variants, the models have r...
详细信息
The cyclic hoist scheduling problem (CHSP) is a well-studied optimisation problem due to its importance in industry. Despite the wide range of solving techniques applied to the CHSP and its variants, the models have remained complicated and inflexible, or have failed to scale up with larger problem instances. This article re-examines modelling of the CHSP and proposes a new simple, flexible constraint programming formulation. We compare current state-of-the-art solving technologies on this formulation, and show that modelling in a high-level constraint language, MiniZinc, leads to both a simple, generic model and to computational results that outperform the state of the art. We further demonstrate that combining integer programming and lazy clause generation, using the multiple cores of modern processors, has potential to improve over either solving approach alone.
暂无评论