Mohammad Mahdavi Mazdeh, Ali Khan Nakhjavani , Abalfazl Zareei,
Volume 21, Issue 2 (IJIEPR 2010)
Abstract
This paper deals with minimization of tardiness in single machine scheduling problem when each job has two different due-dates i.e. ordinary due-date and drop dead date. The drop dead date is the date in which jobs’ weights rise sharply or the customer cancels the order. A linear programming formulation is developed for the problem and since the problem is known to be NP-hard, three heuristic algorithms are designed for the problem based on Tabu search mechanism. Extensive numerical experiments were conducted to observe and compare the behavior of the algorithms in solving the problem..
Seyed Mohammad Seyedhosseini, Mohammad Mahdavi Mazdeh, Dr. Ahmad Makui, Seyed Mohammad Ghoreyshi,
Volume 27, Issue 1 (IJIEPR 2016)
Abstract
In any supply chain, distribution planning of products is of great importance to managers. With effective and flexible distribution planning, mangers can increase the efficiency of time, place, and delivery utility of whole supply chain. In this paper, inventory routing problem (IRP) is applied to distribution planning of perishable products in a supply chain. The studied supply chain is composed of two levels a supplier and customers. Customers’ locations are geographically around the supplier location and their demands are uncertain and follow an independent probability distribution functions. The product has pre-determined fixed life and is to be distributed among customers via a fleet of homogenous vehicles. The supplier uses direct routes for delivering products to customers. The objective is to determine when to deliver to each customer, how much to deliver to them, and how to assign them to vehicle and routes. The mentioned problem is formulated and solved using a stochastic dynamic programming approach. Also, a numerical example is given to illustrate the applicability of proposed approach.
Simin Dargahi Darabad, Maryam Izadbakhsh, Seyed Farid Ghannadpour, Siamak Noori, Mohammad Mahdavi Mazdeh,
Volume 35, Issue 1 (IJIEPR 2024)
Abstract
The construction supply chain is presently the focus of considerable interest among numerous project-related businesses. Strong project management is essential for the effective completion of a project, since restricted budgets and time constraints are considered for each project. The research uses multi-objective linear programming to create a mathematical model of the building supply chain. The primary aims of the present investigation are to limit the expenses associated with logistics and to diminish the release of greenhouse gases caused by transportation. Given the reality of managing several projects concurrently, the model provided comprises a network of projects. Following the completion of each project, an inspection is arranged to assess its level of success. Estimating the costs of a project relies on several variables. In reality, there are always uncertainties highlighted in several studies about the uncertainty of cost and time parameters. This research incorporates many characteristics concurrently to simulate real-world settings and address the issue of uncertainty. The expression of uncertainty for all costs, activity length, inspection, supplier capacity, and resource demand are represented by triangular fuzzy numbers. Ultimately, the precision of the model's performance has been verified using a numerical illustration.
