Showing 3 results for Time Windows
S.m. Seyed-Hosseini, M. Sabzehparvar, S. Nouri ,
Volume 18, Issue 3 (11-2007)
Abstract
Abstract: This paper presents an exact model and a genetic algorithm for the multi-mode resource constrained project scheduling problem with generalized precedence relations in which the duration of an activity is determined by the mode selection and the duration reduction (crashing) applied within the selected mode. All resources considered are renewable. The objective is to determine a mode, the amount of continuous crashing, and a start time for each activity so that all constraints are obeyed and the project duration is minimized. Project scheduling of this type occurs in many fields for instance, predicting the resources and duration of activities in software development projects. A key feature of the model is that none of the typical models can cope with the continuous resource constraints. Computational results with a set of 100 generated instances have been reported and the efficiency of the proposed model has been analyzed.
Hadi Karimi, Abbas Seifi,
Volume 23, Issue 4 (11-2012)
Abstract
The analytic center cutting plane method (ACCPM) is one of successful methods to solve nondifferentiable optimization problems. In this paper ACCPM is used for the first time in the vehicle routing problem with time windows (VRPTW) to accelerate lagrangian relaxation procedure for the problem. At first the basic cutting plane algorithm and its relationship with column generation method is clarified then the new method based on ACCPM is proposed as a stabilization technique of column generation (lagrangian relaxation). Both approaches are tested on a benchmark instance to demonstrate the advantages of proposed method in terms of computational time and lower bounds quality.
Hossein Jandaghi, Ali Divsalar, Mohammad Mahdi Paydar,
Volume 30, Issue 1 (3-2019)
Abstract
In this research, a new bi-objective routing problem is developed in which a conventional vehicle routing problem with time windows (VRPTW) is considered with environmental impacts and heterogeneous vehicles. In this problem, minimizing the fuel consumption (liter) as well as the length of the routes (meter) are the main objectives. Therefore, a mathematical bi-objective model is solved to create Pareto's solutions. The objectives of the proposed mathematical model are to minimize the sum of distance cost as well as fuel consumption and Co2 emission. Then, the proposed Mixed-Integer Linear Program (MILP) is solved using the ε-constraint approach Furthermore, numerical tests performed to quantify the benefits of using a comprehensive goal function with two different objectives. Managerial insights and sensitivity analysis are also performed to show how different parameters of the problem affect the computational speed and the solutions’ quality.
