Showing 5 results for Resource Constraint
Mohammad Reisi, Ghasem Moslehi,
Volume 24, Issue 4 (12-2013)
Abstract
Increasing competition in the air transport market has intensified active airlines’ efforts to keep their market share by attaching due importance to cost management aimed at reduced final prices. Crew costs are second only to fuel costs on the cost list of airline companies. So, this paper attempts to investigate the cockpit crew pairing problem. The set partitioning problem has been used for modelling the problem at hand and, because it is classified in large scale problems, the column generation approach has been used to solve LP relaxation of the set partitioning model. Our focus will be on solving the column generation sub-problem. For this purpose, two algorithms, named SPRCF and SPRCD, have been developed based on the shortest path with resource constraint algorithms. Their efficiency in solving some problem instances has been tested and the results have been compared with those of an algorithm for crew pairing problem reported in the literature. Results indicate the high efficiency of the proposed algorithms in solving problem instances with up to 632 flight legs in a reasonable time.
Parham Azimi, Naeim Azouji,
Volume 28, Issue 4 (11-2017)
Abstract
In this paper a novel modelling and solving method has been developed to address the so-called resource constrained project scheduling problem (RCPSP) where project tasks have multiple modes and also the preemption of activities are allowed. To solve this NP-hard problem, a new general optimization via simulation (OvS) approach has been developed which is the main contribution of the current research. In this approach, the mathematical model of the main problem is relaxed and solved then the optimum solutions were used in the corresponding simulation model to produce several random feasible solutions for the main problem. Finally, the most promising solutions were selected as the initial population of a genetic Algorithm (GA). To test the efficiency of the problem, several test problems were solved by the proposed approach and according to the results, the proposed concept has a very good performance to solve such a complex combinatoral problem. Also, the concept could be easily applied for other similar combinatorics.
Rana Imannezhad, Soroush Avakh Darestani,
Volume 29, Issue 3 (9-2018)
Abstract
Project scheduling problem with resources constraint is a well-known problem in the field of project management. The applicable nature of this problem has caused the researchers’ tendency to it. In this study, project scheduling with resource constraints and the possibility of interruption of project activities as well as renewable resources constraint has been also applied along with a case study on construction projects. Construction projects involve complex levels of work. Making wrong decisions in selecting methods and how to allocate the necessary resources such as manpower and equipment can lead to the results such as increasing the predetermined cost and time. According to NP-Hard nature of the problem, it is very difficult or even impossible to obtain optimal solution using optimization software and traditional methods. In project scheduling using CPM method, critical path is widely used; however, in this method, the resource constraints is not considered. Project Scheduling seek proper sequence for doing the project activities. This study has been conducted using Bees meta-heuristic algorithm, with the aim of optimizing the project completion time. Finally, the results obtained from three algorithms and GAMS software shows that this algorithm has better performance than and the solution among the other algorithms and has achieved the accurate solutions.
Parham Azimi, Shahed Sholekar,
Volume 32, Issue 1 (1-2021)
Abstract
According to the real projects’ data, activity durations are affected by numerous parameters. In this research, we have developed a multi-resource multi objective multi-mode resource constrained scheduling problem with stochastic durations where the mean and the standard deviation of activity durations are related to the mode in which each activity is performed. The objective functions of model were to minimize the net present value and makespan of the project. A simulation-based optimization approach was used to handle the problem with several stochastic events. This feature helped us to find several solutions quickly while there was no need to take simplification assumptions. To test the efficiency of the proposed algorithm, several test problems were taken from the PSPLIB directory and solved. The results show the efficiency of the proposed algorithm both in quality of the solutions and the speed.
Amir Nayeb, Esmaeil Mehdizadeh, Seyed Habib A. Rahmati,
Volume 34, Issue 2 (6-2023)
Abstract
In the field of scheduling and sequence of operations, one of the common assumptions is the availability of machines and workers on the planning horizon. In the real world, a machine may be temporarily unavailable for a variety of reasons, including maintenance activities, and the full capacity of human resources cannot be used due to their limited number and/or different skill levels. Therefore, this paper examines the Dual Resource Constrained Flexible Job Shop Scheduling Problem (DRCFJSP) considering the limit of preventive maintenance (PM). Due to various variables and constraints, the goal is to minimize the maximum completion time. In this regard, Mixed Integer Linear Programming (MILP) model is presented for the mentioned problem. To evaluate and validate the presented mathematical model, several small and medium-sized problems are randomly generated and solved using CPLEX solver in GAMS software. Because the solving of this problem on a large scale is complex and time-consuming, two metaheuristic algorithms called Genetic Algorithm (GA) and Vibration Damping Optimization Algorithm (VDO) are used. The computational results show that GAMS software can solve small problems in an acceptable time and achieve an accurate answer, and also meta-heuristic algorithms can reach appropriate answers. The efficiency of the two proposed algorithms is also compared in terms of computational time and the value obtained for the objective function.
