Mojahid F. Saeed Osman

Radio frequency identification system optimisation models for lifecycle of a durable product

We address the implementation of radio frequency identification (RFID) technology to support and manage durable products over their entire lifecycle with a focus on optimising the RFID tagging system. We develop general models that optimise the placement of RFID tags on an end product and its components, the allocation of the data on tags, and the selection of RFID tags and their configuration. The primary criteria for optimisation are to maximise the value of RFID data, and to minimise the total cost of the RFID tag system. The total cost of RFID tags comprises costs associated with memory capacity, tag type, software acquisition and maintenance, and number of tags used; the total value for a piece of data is determined by the data usage frequency and the fixed and variable value of data per use across the product lifecycle. The tag placement and data allocation model involves making a decision about these two different objectives–cost and value, which we develop in the form of a multi-objective optimisation problem. The tag selection model aids in the proper selection of RFID tags and their configuration for individual components for a given end product. Given a durable products characteristics along with its bill-of-materials, a system of RFID tags can efficiently be determined for the product and its components, to help manage and support its lifecycle.

Short Communication: Two-phase evacuation route planning approach using combined path networks for buildings and roads

This paper addresses the problem of modeling evacuation routes from a building and out of an affected area. The evacuation route involves pathways such as corridors, and stairs in buildings and road networks and sidewalks outside the building. To illustrate such an approach, we consider the problem of finding evacuation paths from an urban building and out of a predetermined neighborhood of the building on foot. A case study for a college campus building and small set of road around it is provided. There are a pre-defined set of exit points out of the target building and out of the road network serving the building. A two-step approach with an uncapacitated network model for route finding and a capacitated scheduling algorithm for evacuation time computation is proposed. A recent efficient heuristic algorithm is selected as a reference for comparative analysis. The process of creating a combined building and road path network data is discussed. The key results are the competitive evacuation time provided by the proposed uncapacitated route planning model, simple pedestrian flow capacity formulas for corridors and roads from readily available geometric data, and the illustration of the creation and use of combined building and road path network.

Evacuation route scheduling using discrete time-based Capacity-Constrained model

This paper addresses the problem of modeling evacuation scheduling out of an affected area. There are a pre-defined set of exit points out of the target affected area and a set of source points for the evacuees. We propose an optimization model for evacuation scheduling; this approach models the capacity-constrained evacuation scheduling problem over discrete time as an integer optimization model. A recent efficient heuristic for evacuation planning, Capacity-Constrained Route Planning (CCRP) algorithm is selected as a reference for comparison. The result on a sample problem shows that the proposed model is competitive with the CCRP heuristic in terms of the resulting evacuation time and evacuation routes and schedules.

Optimization Model For Distributed Routing For Disaster Area Logistics

The problem of transportation in a disaster area can be seen broadly as having two aspects: (a) moving people and materials out of an area, and (b) moving people and materiel into the same area. The common thread here is the use of a limited set of surface and air transportation gateways into and out of the area. The distributed routing problem here is that of assigning one from among the limited set of gateways to various transportation requests in real-time, while maximizing some measure of success for the entire relief mission. We define the general problem, provide an example of the real-time transportation routing problem, and propose an optimization model. The similarity of this problem to a job shop scheduling problem is presented pointing to the fact that a distributed approach based on bio-inspired methods can be developed to counter the large problem size and centralized nature of the integer multi-commodity network model. A small illustrative model of the integer multi-commodity network model is presented and solved

Dynamic Scheduling for Batch Data Processing in Parallel Systems

In many operations time factor is a main constraint. Being able to optimally execute them while minimizing the amount of resources used remain a challenge in many business areas. In this paper we propose a model to optimally schedule processing a set of tasks which are part of network of operations on processors that are all capable of handling these tasks. The objective is to process these tasks and operations within a cut-off time while satisfying all the precedence constraints using the minimum number of resources, i.e. processors.

Assignment-based MIP Modeling for Solving a Selling Firm mTSP with Time Limit Constraints

This paper presents a version of the multiple traveling salesmen problem with service time limit constraints and travel times. The time required to provide merchandising service at any outlet location is predetermined based on the customer type. The objective is to minimize the number of salesmen hired by a selling firm while visiting and providing services to all customers without exceeding salesmen’s allowed working times. The paper proposes an assignment-based mixed integer programming model for solving the salesmen problem of a selling firm that applies a sub-tour elimination restriction. A case example is presented for illustrating the applicability and suitability of the proposed approach for solving the problem tackled in this

Distributed scheduling approach for dynamic evacuation networks

ABSTRACT The aim of this paper is to propose a novel distributed scheduling model for evacuation route scheduling from buildings and out of an affected area. The model is based on a hybrid approach that is spatio-temporal algorithm with optimization models as subproblems. The proposed distributed scheduling approach is an iterative process optimizing the one-step arrival of objects to each intermediate destination nodes at a time. To illustrate such an approach, we consider the problem of finding and scheduling evacuation paths from an urban building and out of a predetermined neighbourhood of the building on foot; the evacuation route involves pathways such as corridors, and stairs in buildings and road networks and sidewalks outside the building, there is a predefined set of exit points out of the target building and out of the road network serving the building. A well-known efficient heuristic algorithm is selected as a reference for comparative analysis and to illustrate the outperformance of the proposed approach in large-scale scenarios. The key results are the step-based optimal route schedules and the competitive evacuation time provided by the proposed distributed scheduling approach.

Routing and scheduling on evacuation path networks using centralized hybrid approach

Abstract We examine the problem of finding evacuation routes from an urban building and out of its predetermined neighborhood. We propose a centralized hybrid approach for time-dependent point-to-point evacuation routing and scheduling, which is a novel spatio-temporal algorithm with discrete optimization models as sub problems. This algorithm does account for node and arc capacities and objects in transit over dynamic networks for routing and scheduling in a deterministic setting. A recent efficient method is selected for comparative analysis. For conducting this analysis, we used real case problems for finding evacuation paths from a building and out of a predetermined neighborhood of the building. The key results reveal the effectiveness of the proposed centralized hybrid approach for solving evacuation routing and scheduling problems.

Maintenance data allocation model for Repairable Items in echelon inventory system

This paper addresses the implementation of Automated Identification Technologies (AIT) to support and manage the maintenance of repairable equipment and components that are intended for relatively long use in echelon inventory system with the aim of optimizing the data allocation in a given automated identification system. The paper presents the development of general model for optimizing the use of AIT system for repairable equipment and items, and the allocation of preventive and corrective maintenance data on tags. The primary criterion for optimization is to maximize the value of maintenance data while not exceeding the available data capacity of the AIT system. The value of maintenance data through the life cycle of repairable equipment and items is determined by the variable value of data per use that varies based on its frequency of usage and its basic fixed value.

Route finding procedures for performing distribution routing function in supply chain

In supply chain management, distribution routing is a key transportation routing function. This function involves determining the geographic route a vehicle will travel to reach the delivery destination. In this paper we develop a solution procedure to guide the problem-solving process and quickly leads to a good routing solution of the distribution operations with an objective of minimizing the transportation cost via minimizing the total distance travelled while satisfying demand and capacity constraints.