eng
Iranian Institute of Industrial Engineering
Journal of Industrial and Systems Engineering
1735-8272
2717-3380
2007-09-01
1
2
97
115
3921
Strategies to Overcome Network Congestion in Infrastructure Systems
Jason W. Black
1
Richard C. Larson
2
Center for Engineering Systems Fundamentals; Engineering Systems Division Massachusetts Institute of Technology; Cambridge, Massachusetts 02139 USA
Center for Engineering Systems Fundamentals; Engineering Systems Division Massachusetts Institute of Technology; Cambridge, Massachusetts 02139 USA
Networked Infrastructure systems deliver services and/or products from point to point along the network. Demand for the services provided by such systems is typically cyclic, creating inefficiencies in capacity utilization. Congestion pricing provides incentives to shift demand from peak time periods to lower demand periods. This effectively increases the capacity of the system without the need for additional capital investment. This paper investigates the potential for congestion pricing to reduce necessary infrastructure investments in the United States. Several types of congestion pricing schemes are presented, along with existing implementations across multiple infrastructure systems. We find over $20 billion in potential annual savings in electricity and road systems alone in the United States from implementing congestion pricing schemes.
https://www.jise.ir/article_3921_0826543f09926b2d6f95f47c8a2b16ef.pdf
Networked infrastructure systems
Congestion Pricing
Capacity utilization
eng
Iranian Institute of Industrial Engineering
Journal of Industrial and Systems Engineering
1735-8272
2717-3380
2007-09-01
1
2
116
129
3922
A Possibility Linear Programming Approach to Solve a Fuzzy Single Machine Scheduling Problem
I.N. Kamalabadi
1
A.H. Mirzaei
2
B. Javadi
3
1Department of Industrial Engineering, Faculty of Engineering, University of Kurdistan, Sanandaj, Iran
Department of Industrial Engineering, Faculty of Engineering, Tarbiat Modares University
Department of Industrial Engineering, Mazandaran University of Science and Technology
This paper employs an interactive possibility linear programming approach to solve a single machine scheduling problem with imprecise processing times, due dates, as well as earliness and tardiness penalties of jobs. The proposed approach is based on a strategy of minimizing the most possible value of the imprecise total costs, maximizing the possibility of obtaining a lower total costs, and minimizing the risk of obtaining higher total costs simultaneously. This approach is applicable to just-in-time systems, in which many firms face the need to complete jobs as close as possible to their due dates. The objective of the model is to minimize the total costs of earliness/tardiness penalties. In this paper, the proposed possibility linear programming approach is applied to a fuzzy single machine scheduling problem with respect to the overall degree of decision maker satisfaction. Due to the proposed model’s complexity, conventional optimization methods cannot be utilized in reasonable time. Hence, the particle swarm optimization method is applied toward its solution.
https://www.jise.ir/article_3922_bc6e60fa8368ccc24108f6c6e004a714.pdf
Single machine scheduling
Earliness / tardiness
Possibility linear programming
Particle Swarm Optimization
eng
Iranian Institute of Industrial Engineering
Journal of Industrial and Systems Engineering
1735-8272
2717-3380
2007-09-01
1
2
130
138
3923
Price Discount and Stochastic Initial Inventory in the Newsboy Problem
Maryam Haji
1
Rasoul Haji
2
Houshang Darabi
3
1Dept. of Mech. and Ind. Eng. University of Illinois at Chicago, Chicago, IL, 60607, USA
Dept. of Ind. Eng. Sharif University of Technology, Tehran, Iran
Dept. of Mech. and Ind. Eng. University of Illinois at Chicago, Chicago, IL, 60607, USA
Many extension of the newsboy problem have been solved in the literature. One of those extensions solves a newsboy problem with stochastic initial inventory, earlier extensions have focused on quantity discounts offered by suppliers. An important practical extension would address a combination of the two pervious extensions. In this paper we consider a newsboy problem in which the suppliers offer quantity discount and the initial inventory at the beginning of the period is a random variable. We obtain the optimal value of the order quantity which maximizes the total profit and then present the results for some practical distributions of both random variables, demand and initial inventory.
https://www.jise.ir/article_3923_32fd0b80aa077d13466aee54f11a6201.pdf
Stochastic initial inventory
Newsboy problem
Inventory management
Supplier
discount
eng
Iranian Institute of Industrial Engineering
Journal of Industrial and Systems Engineering
1735-8272
2717-3380
2007-09-01
1
2
139
150
3924
An Evaluation of Mahalanobis-Taguchi System and Neural Network for Multivariate Pattern Recognition
Elizabeth A. Cudney
1
Jungeui Hong
2
Rajesh Jugulum
3
Kioumars Paryani
4
Kenneth M. Ragsdell
5
Genichi Taguchi
6
University of Missouri – Rolla, Rolla, Missouri 65409 U.S.A.
Chungju National University, Chungju, 380-702 South Korea
Massachusetts Institute of Technology, Cambridge, Massachusetts 02139 U.S.A.
Lawrence Technological University, Southfield, Michigan, U.S.A.
University of Missouri – Rolla, Rolla, Missouri 65409 U.S.A.
Ohken Associates, Tokyo, Japan
The Mahalanobis-Taguchi System is a diagnosis and predictive method for analyzing patterns in multivariate cases. The goal of this study is to compare the ability of the Mahalanobis- Taguchi System and a neural-network to discriminate using small data sets. We examine the discriminant ability as a function of data set size using an application area where reliable data is publicly available. The study uses the Wisconsin Breast Cancer study with nine attributes and one class.
https://www.jise.ir/article_3924_5f31f4ac2ae98ac31c98b527e637819e.pdf
Mahalanobis-Taguchi System
Mahalanobis distance
Neural Network
Pattern
recognition
Orthogonal array
Signal-to-noise ratio
Mahalanobis space (reference group)
eng
Iranian Institute of Industrial Engineering
Journal of Industrial and Systems Engineering
1735-8272
2717-3380
2007-09-01
1
2
151
170
3925
A Comparative Study of Exact Algorithms for the Two Dimensional Strip Packing Problem
Abdelghani Bekrar
1
Imed Kacem
2
Chengbin Chu
3
ICD-LOSI, (CNRS FRE 2848) UNIVERSITE DE TECHNOLOGIE DE TROYES FRANCE
ICD-LOSI, (CNRS FRE 2848) UNIVERSITE DE TECHNOLOGIE DE TROYES FRANCE
ICD-LOSI, (CNRS FRE 2848) UNIVERSITE DE TECHNOLOGIE DE TROYES FRANCE
In this paper we consider a two dimensional strip packing problem. The problem consists of packing a set of rectangular items in one strip of width W and infinite height. They must be packed without overlapping, parallel to the edge of the strip and we assume that the items are oriented, i.e. they cannot be rotated. To solve this problem, we use three exact methods: a branch and bound method, a dichotomous algorithm and a branch and price method. The three methods were carried out and compared on literature instances.
https://www.jise.ir/article_3925_c0e029a3afa0c02dd4ecd8426daea585.pdf
Strip packing
lower and upper bound
Branch and bound
dichotomous search
column generation
branch and price
eng
Iranian Institute of Industrial Engineering
Journal of Industrial and Systems Engineering
1735-8272
2717-3380
2007-09-01
1
2
171
189
3926
Fuzzy Hierarchical Location-Allocation Models for Congested Systems
Hassan Shavandi
1
Hashem Mahlooji
2
Department of Industrial Engineering , Sharif University of Technology Tehran , Iran
Department of Industrial Engineering , Sharif University of Technology Tehran , Iran
There exist various service systems that have hierarchical structure. In hierarchical service networks, facilities at different levels provide different types of services. For example, in health care systems, general centers provide low-level services such as primary health care services, while the specialized hospitals provide high-level services. Because of demand congestion in service networks, location of servers and allocation of demand nodes have a strong impact on the length of queues at servers as well as on the response times to service calls. The thrust of this article is the development of hierarchical location-allocation models for congested systems by employing queueing theory in a fuzzy framework. The new models allow partial coverage of demand nodes and approximate determination of parameters. Using queueing theory and fuzzy conditions, both referral and nested hierarchical models are developed for the maximal covering location problem (MCLP). An example is solved for both an existing probabilistic model and the new fuzzy models and the results are compared.
https://www.jise.ir/article_3926_f5ad283c3686e617c9dc96d75782144c.pdf
Location
Hierarchical
Queueing
Fuzzy Sets
Congested Systems
Referral
systems
Nested systems