Showing 20 results for Demand
A. Shariat Mohaymany , S.m.mahdi Amiripour,
Volume 20, Issue 3 (9-2009)
Abstract
Local bus network is the most popular transit mode and the only available transit mode in the majority of cities of the world. Increasing the utility of this mode which increases its share from urban trips is an important goal for city planners. Timetable setting as the second component of bus network design problem (network route design timetable setting vehicle assignment crew assignment) have a great impact on total travel time of transit passengers. The total travel time would effect on transit utility and transit share of urban trips. One of the most important issues in timetable setting is the temporal coverage of service during the day. The coverage of demand is an objective for setting timetables which has not been well studied in the literature. In this paper a model is developed in order to maximize the temporal coverage of bus network. The model considers demand variation during the day as well as the stochastic nature of demand. A distribution function is used instead of a deterministic value for demand. The model is then implemented to an imaginary case.
Hossein Sadeghi, Mahdi Zolfaghari , Mohamad Heydarizade,
Volume 22, Issue 1 (3-2011)
Abstract
This paper aimed at estimation of the per capita consumption of electricity in residential sector based on economic indicators in Iran. The Genetic Algorithm Electricity Demand Model (GAEDM) was developed based on the past data using the genetic algorithm approach (GAA). The economic indicators used during the model development include: gross domestic product (GDP) in terms of per capita and real price of electricity and natural gas in residential sector. Three forms of GAEDM were developed to estimate the electricity demand. The developed models were validated with actual data, and the best estimated model was selected on base of evaluation criteria. The results showed that the exponential form had more precision to estimate the electricity demand than two other models. Finally, the future estimation of electricity demand was projected between 2009 and 2025 by three forms of the equations linear, quadratic and exponential under different scenarios .
M. Miranbeigi, A.a. Jalali, A. Miranbeigi ,
Volume 22, Issue 3 (9-2011)
Abstract
supply chain network receding horizon control demand move suppression term |
Supply chain networks are interconnection and dynamics of a demand network. Example subsystems, referred to as stages, include raw materials, distributors of the raw materials, manufacturers, distributors of the manufactured products, retailers, and customers. The main objectives of the control strategy for the supply chain network can be summarized as follows: (i) maximize customer satisfaction, and (ii) minimize supply chain operating costs. In this paper, we applied receding horizon control (RHC) method to a set of large scale supply chains of realistic size under demand disturbances adaptively. Also in order to increase the robustness of the system , we added a move suppression term to cost function .
Mostafa Hajiaghaei-Keshteli, Majid Aminnayeri,
Volume 23, Issue 4 (11-2012)
Abstract
In this paper, the cost function for a three-echelon inventory system with two warehouses is derived. Transportation times are constant and retailers face independent Poisson demand. Replenishments are one-for-one. The lead time of a retailer is determined not only by the constant transportation time but also by the random delay incurred due to the availability of stock at the warehouses. We consider two warehouses in the second echelon which may leads to having more delays which were incurred in the warehouses and facing different behaviors of independent Poisson demands. Because the replenishment policy is base stock, the obtained function can also be used in different ordering policies to compute the inventory holding and shortage costs.
Masoud Mahootchi, Taher Ahmadi, Kumaraswamy Ponnambalam,
Volume 23, Issue 4 (11-2012)
Abstract
This paper presents a new formulation for warehouse inventory management in a stochastic situation. The primary source of this formulation is derived from FP model, which has been proposed by Fletcher and Ponnambalam for reservoir management. The new proposed mathematical model is based on the first and the second moments of storage as a stochastic variable. Using this model, the expected value of storage, the variance of storage, and the optimal ordering policies are determined. Moreover, the probability of within containment, surplus, and shortage are computable without adding any new variables. To validate the optimization model, a Monte Carlo simulation is used. Furthermore, to evaluate the performance of the optimal FP policy, It is compared to (s*,S*) policy, as a very popular policy used in the literature, in terms of the expected total annual cost and the service level. It is also demonstrated that the FP policy has a superior performances than (s*,S*) policy.
M. Ameli, A. Mirzazadeh, M. Shirazi,
Volume 24, Issue 1 (2-2013)
Abstract
It was suggested in 2004 by some researchers that it might be possible to improve production systems performance by applying the first and second laws of thermodynamics to reduce system entropy. Then these laws were used to modify the economic order quantity (EOQ) model to derive an equivalent entropic order quantity (EnOQ). Moreover the political instability or uncertainty of a country (as well as the whole world) leads to a much more unstable situation in the present world economy. Thus, changes in inflation take place, and it is needed to consider uncertain inflation rate. In this paper we extend the EnoQ model by considering deteriorating items with imperfect quality and price dependent demand. We also assume fuzzy inflation and discount rates. A mathematical model is developed to determine the number of cycles that maximizes the present value of total revenue in a finite planning horizon. The fuzzified model for inflation and discount rate is formulated and solved by two methods: signed distance and fuzzy numbers ranking. Numerical examples are presented and results are discussed. Results show that the number of cycles decreases in fuzzy inflationary conditions. They also illustrate that defuzzification method results in more cycles than fuzzy method.
Sanchita Sarkar, Tripti Tripti Chakrabarti,
Volume 24, Issue 4 (12-2013)
Abstract
In the fundamental production inventory model, in order to solve the economic production quantity (EPQ) we always fix both the demand quantity and the production quantity per day. But, in the real situation, both of them probably will have little disturbances every day. Therefore, we should fuzzify both of them to solve the economic production quantity (q*) per cycle. Using α-cut for defuzzification the total variable cost per unit time is derived. Therefore the problem is reduced to crisp annual costs. The multi-objective model is solved by Global Criteria Method with the help of GRG (Generalized Reduced Gradient) Technique. In this model shortages are permitted and fully backordered. The purpose of this paper is to investigate a computing schema for the EPQ in the fuzzy sense. We find that, after defuzzification, the total cost in fuzzy model is less than in the crisp model. So it permits better use of the EPQ model in the fuzzy sense arising with little disturbances in the production, and demand.
Yahia Zare Mehrjerdi, Ali Nadizadeh,
Volume 27, Issue 1 (3-2016)
Abstract
Using Greedy Clustering Method to Solve Capacitated Location-Routing Problem with Fuzzy Demands Abstract In this paper, the capacitated location routing problem with fuzzy demands (CLRP_FD) is considered. In CLRP_FD, facility location problem (FLP) and vehicle routing problem (VRP) are observed simultaneously. Indeed the vehicles and the depots have a predefined capacity to serve the customersthat have fuzzy demands. To model the CLRP_FD, a fuzzy chance constrained program is designed, based on fuzzy credibility theory. To solve the CLRP_FD, a greedy clustering method (GCM) including the stochastic simulation is proposed. Finally, to obtain the best value of the preference index of the model and analysis its influence on the final solutions of the problem, numerical experiments are carried out. Keywords: Capacitated location routing problem, Fuzzy demand, Credibility theory, Stochastic simulation, Ant colony system.
Ramin Sadeghian,
Volume 27, Issue 2 (6-2016)
Abstract
Generally ordering policies are done by two methods, including fix order quantity (FOQ) and fix order period (FOP). These methods are static and either the quantity of ordering or the procedure of ordering is fixing in throughout time horizon. In real environments, demand is varying in any period and may be considered as uncertainty. When demand is variable in any period, the traditional and static ordering policies with fix re-order points cannot be efficient. On the other hand, sometimes in real environments some costs may not be well-known or precise. Some costs such as holding cost, ordering cost and so on. Therefore, using the cost based inventory models may not be helpful. In this paper, a model is developed which can be used in the cases of stochastic and irregular demand, and also unknown costs. Also some attributes consisting of expected positive inventory level, expected negative inventory level and inventory confidence level are considered as objective functions instead the objective function of total inventory cost. A numerical example is also presented for more explanation.
Firoozeh Kaveh, Reza Tavakkoli-Moghaddam, Amin Jamili, Maryam Eghbali,
Volume 27, Issue 4 (12-2016)
Abstract
This paper presents a bi-objective capacitated hub arc location problem with single assignment for designing a metro network with an elastic demand. In the literature, it is widely supposed that the network created with the hub nodes is complete. In this paper, this assumption is relaxed. Moreover, in most hub location problems, the demand is assumed to be static and independent of the location of hubs. However, in real life problems, especially for locating a metro hub, the demand is dependent on the utility that is proposed by each hub. By considering the elasticity of demand, the complexity of solving the problem increases. The presented model also has the ability to compute the number of trains between each pair of two hubs. The objectives of this model are to maximize the benefits of transportation and establishing the hub facilities while minimizing the total transportation time. Furthermore, the bi-objective model is converted into a single objective one by the TH method. The significance of applicability of the developed model is demonstrated by a number of numerical experiments and some sensitivity analyses on the data inspired by the Qom monorail project. Finally, the conclusion is provided.
Nita Shah, Chetan Vaghela,
Volume 28, Issue 2 (6-2017)
Abstract
Abstract
In this research, an integrated inventory model for non-instantaneous deteriorating items is analyzed when demand is sensitive to changes in price. The price used in this research is a time-dependent function of the initial selling price and the discount rate. To control the deterioration rate of items at the storage facility, investment in preservation technology is incorporated. To provide a general framework to the model, an arbitrary holding cost rate is used. Toward the end of the paper, a numerical case is given to approve the model and the impacts of the key parameters of the model are studied by sensitivity analysis to deduce managerial insights.
Ali Nadizadeh,
Volume 28, Issue 3 (9-2017)
Abstract
In this paper, the fuzzy multi-depot vehicle routing problem with simultaneous pickup and delivery (FMDVRP-SPD) is investigated. The FMDVRP-SPD is the problem of allocating customers to several depots, so that the optimal set of routes is determined simultaneously to serve the pickup and the delivery demands of each customer within scattered depots. In the problem, both pickup and delivery demands of customers are fuzzy variables. The objective of FMDVRP-SPD is to minimize the total cost of a distribution system including vehicle traveling cost and vehicle fixed cost. To model the problem, a fuzzy chance-constrained programming model is proposed based on the fuzzy credibility theory. A heuristic algorithm combining K-means clustering algorithm and ant colony optimization is developed for solving the problem. To achieve an appropriate threshold value of parameters of the model, named “vehicle indexes”, and to analyze their influences on the final solution, numerical experiments are carried out.
Amin Saghaeeian, Reza Ramezanian,
Volume 28, Issue 4 (11-2017)
Abstract
This study considers pricing, production and transportation decisions in a Stackelberg game between three-stage, multi-product, multi-source and single-period supply chains called leader and follower. These chains consist of; manufacturers, distribution centers (DCs) and retailers. Competition type is horizontal and SC vs. SC. The retailers in two chains try to maximize their profit through pricing of products in different markets and regarding the transportation and production costs. A bi-level nonlinear programming model is formulated in order to represent the Stackelberg game. Pricing decisions are based on discrimination pricing rules, where we can put different prices in different markets. After that the model is reduced to single-level nonlinear programming model by replacing Karush-Kuhn-Tucker conditions for the lower level (follower) problem. Finally, a numerical example is solved in order to analyze the sensitivity of effective parameters on price and profit.
Sasan Khalifehzadeh, Mohammad Bagher Fakhrzad,
Volume 29, Issue 3 (9-2018)
Abstract
Abstract
Production and distribution network (PDN) planning in multi-stage status is commonly complex. These conditions cause significant amount of uncertainty relating to demand and lead time. In this study, we introduce a PDN to deliver the products to customers in the least time and optimize the total cost of the network, simultaneously. The proposed network is four stage PDN including suppliers, producers, potential entrepots, retailers and customers with multi time period horizon with allowable shortage. A mixed integer programming model with minimizing total cost of the system and minimizing total delivery lead time is designed. We present a novel heuristic method called selective firefly algorithm (SFA) in order to solve several sized especially real world instances. In SFA, each firefly recognizes all better fireflies with more brightness and analyses its brightness change before moving, tacitly. Then, the firefly that makes best change is selected and initial firefly moves toward the selected firefly. Finally, the performance of the proposed algorithm is examined with solving several sized instances. The results indicate the adequate performance of the proposed algorithm.
Sujata Saha, Tripti Chakrabarti,
Volume 32, Issue 3 (9-2021)
Abstract
This paper aims to frame a two-player supply chain model with a production system's reliability influenced products’ defection rate. Upon generating and inspecting the products, the producer reworks the defectives and sells the perfect and reworked items to a retailer providing him free products' delivery. The retailer stores both types of commodities in the respective showrooms of finite capacities and keeps the excess conforming products in a leased warehouse. Eventually, the formulation of these two partners' profit functions performed, and a numerical illustration demonstrates this model's applicability. Results shows, hiring a storehouse is profitable for the retailer and the deterioration of the production system’s reliability impacts adversely on the manufacturer's profit.
Fatemeh Faghidian, Mehdi Khashei, Mohammad Khalilzadeh,
Volume 33, Issue 1 (3-2022)
Abstract
This study seeks to introduce the influential factors in controlling and dealing with uncertainty in intermittent demand. Hybrid forecasting and Grey Theory, due to their potential in facing complex nature, insufficient data, have been used simultaneously. Different modeling, unbiased weighting results have been used in estimating the safety stock(SS) by both theoretical and experimental methods. In other words, this work deals with the less studied feature of various modeling errors and their effect on SS determination and recommends its use to address the uncertainty of intermittent demand as a criterion for introducing a superior model in the field of inventory.
Hamza Samouche, Abdellah El Barkany, Ahmed Elkhalfi,
Volume 34, Issue 2 (6-2023)
Abstract
Sales and operations planning (S&OP) is considered as an important tool at the planning strategic level. Its models vary depending on industries. The Asian model is known to be very developed. Having several parameters, the Asian model proves to be an effective tool, precisely for the study of capacity. However, after several searches made in various databases, we did not find any concrete model actually used in industry and whose parameters are presented and which defines the analysis logic to better align supply and demand. In this article, we will carry out various simulations on the basis of the data of a model of sales and operations planning used in a wire harnesses factory, in order to explain the decision-making process during S&OP meetings. The parameters of the model and the various constraints that were facing the sales and operations planning team are presented and discussed as well as the financial consequences of certain decisions. As a result of this study, we can notice that S&OP is indeed a powerful tool that makes it possible to detect in advance the various constraints whose resolution concludes in an optimal alignment between customer demand and factory capacity.
Mariam Atwani, Mustapha Hlyal , Jamila El Alami ,
Volume 35, Issue 2 (6-2024)
Abstract
In today's dynamic and competitive manufacturing landscape, accurate demand forecasting is paramount for optimizing production processes, reducing inventory costs, and meeting customer demands efficiently. With the advent of Artificial Intelligence (AI), there has been a significant evolution in demand forecasting methods, enabling manufacturers to enhance the accuracy of the forecasts.
This systematic literature review aims to provide a comprehensive overview of the state-of-the-art on demand forecasting models in the manufacturing sector, whether AI-based models or hybrid methods merging both the AI technology and classical demand forecasting methods. The review begins by establishing an overview on demand forecasting methods, it then outlines the systematic methodology used for the literature search.
The review encompasses a wide range of scholarly articles published up to September 2023. A rigorous screening process is applied to select relevant studies. Accordingly, a thorough analysis in the basis of the forecasting methods adopted and data used have been carried out. By synthesizing the existing knowledge, this review contributes to the ongoing advancement of demand forecasting practices in the manufacturing sector providing researchers and practitioners an overview on the advancements on the use of AI models to improve the accuracy of demand forecasting models.
Iffan Maflahah, Wila Wirvikananda, Hamzah Fansuri, Dian Farida Asfan, Raden Faridz,
Volume 35, Issue 3 (9-2024)
Abstract
Seablite salt (Suaeda maritima) was a unique product currently under development. Seablite is a low-sodium salt essential for modern society, particularly for those who prioritize their health. This investigation aims to employ a dynamic system approach to evaluate the revenue and profit generated by the salt production system. The dynamic systems approach steps: the construction of the causal loop diagram, the development of the stock-and-flow model, the parameterization of the model, the simulation to analyze the system's behavior under various conditions, the verification and validation, the development of policy recommendations, and the conclusion with a summary of the core findings. The model was developed using four submodels: (1) demand, (2) supply, (3) production cost, and (4) revenue. The moderate scenario demonstrates that the salt flow requirements can be satisfied by utilizing the dynamic system to protect the revenue and production costs. It was consistent with the escalating production expenses. According to the optimistic scenario, the salt demand can be satisfied until 2026. The company's revenue is insufficient to cover production costs due to the rise in raw material prices. Farmers begin to reap the rewards in this scenario. It's because the overall revenue exceeds the production costs.
Dwi Kurniawan, Aghnia Nazhiifah Ulhaq, Aditya Fadhilah Althofian, Rubby Nur Rachman,
Volume 35, Issue 4 (12-2024)
Abstract
In industrial and commercial settings, inventory systems often involve managing multiple products with diverse demand patterns, making the direct application of the single-item newsvendor model inefficient. To address this complexity, this study proposes an adaptation of the newsvendor model through demand aggregation, where related items are grouped into a product family. By aggregating demand and financial parameters, the traditional newsvendor approach can be extended to multi-item systems, simplifying the inventory management process. This method was tested in two different case studies—a coffee roaster company and a meatball producer—demonstrating its validity and applicability. The aggregated newsvendor model was found to enhance inventory accuracy and efficiency, reducing random error and improving operational performance. This approach offers a valuable extension of the newsvendor model, with potential for broader application across various industries.
