scholarly journals A route planning framework for smart wearable assistive navigation systems

2021 ◽  
Vol 3 (1) ◽  
Author(s):  
Charis Ntakolia ◽  
Dimitris K. Iakovidis
Keyword(s):  
Programming Model ◽  
Route Planning ◽  
User Preferences ◽  
Navigation Systems ◽  
Individuals With Disabilities ◽  
Planning Framework ◽  
Cultural Spaces ◽  
Nonlinear Programming Model ◽  
System Module ◽  
Smart Wearable

AbstractRoute planning (RP) enables individuals to navigate in unfamiliar environments. Current RP methodologies generate routes that optimize criteria relevant to the traveling distance or time, whereas most of them do not consider personal preferences or needs. Also, most of the current smart wearable assistive navigation systems offer limited support to individuals with disabilities by providing obstacle avoidance instructions, but often neglecting their special requirements with respect to the route quality. Motivated by the mobility needs of such individuals, this study proposes a novel RP framework for assistive navigation that copes these open issues. The framework is based on a novel mixed 0–1 integer nonlinear programming model for solving the RP problem with constraints originating from the needs of individuals with disabilities; unlike previous models, it minimizes: (1) the collision risk with obstacles within a path by prioritizing the safer paths; (2) the walking time; (3) the number of turns by constructing smooth paths, and (4) the loss of cultural interest by penalizing multiple crossovers of the same paths, while satisfying user preferences, such as points of interest to visit and a desired tour duration. The proposed framework is applied for the development of a system module for safe navigation of visually impaired individuals (VIIs) in outdoor cultural spaces. The module is evaluated in a variety of navigation scenarios with different parameters. The results demonstrate the comparative advantage of our RP model over relevant state-of-the-art models, by generating safer and more convenient routes for the VIIs.

scholarly journals Context-aware heatstroke relief station placement and route optimization for large outdoor events

2021 ◽  
Vol 20 (1) ◽  
Author(s):  
Yan Wu ◽  
Tianqi Xia ◽  
Adam Jatowt ◽  
Haoran Zhang ◽  
Xiao Feng ◽  
...  
Keyword(s):  
Physical Environment ◽  
Emergency Service ◽  
Programming Model ◽  
Heterogeneous Data ◽  
Route Optimization ◽  
Mixed Integer ◽  
Context Aware ◽  
Outdoor Activities ◽  
Integer Nonlinear Programming ◽  
Nonlinear Programming Model

Abstract Background Heatstroke is becoming an increasingly serious threat to outdoor activities, especially, at the time of large events organized during summer, including the Olympic Games or various types of happenings in amusement parks like Disneyland or other popular venues. The risk of heatstroke is naturally affected by a high temperature, but it is also dependent on various other contextual factors such as the presence of shaded areas along traveling routes or the distribution of relief stations. The purpose of the study is to develop a method to reduce the heatstroke risk of pedestrians for large outdoor events by optimizing relief station placement, volume scheduling and route. Results Our experiments conducted on the planned site of the Tokyo Olympics and simulated during the two weeks of the Olympics schedule indicate that planning routes and setting relief stations with our proposed optimization model could effectively reduce heatstroke risk. Besides, the results show that supply volume scheduling optimization can further reduce the risk of heatstroke. The route with the shortest length may not be the route with the least risk, relief station and physical environment need to be considered and the proposed method can balance these factors. Conclusions This study proposed a novel emergency service problem that can be applied in large outdoor event scenarios with multiple walking flows. To solve the problem, an effective method is developed and evaluates the heatstroke risk in outdoor space by utilizing context-aware indicators which are determined by large and heterogeneous data including facilities, road networks and street view images. We propose a Mixed Integer Nonlinear Programming model for optimizing routes of pedestrians, determining the location of relief stations and the supply volume in each relief station. The proposed method can help organizers better prepare for the event and pedestrians participate in the event more safely.

Optimum Tool Life and Cutting Speed for the Maximum Productivity at the Drilling of the Steel X6CrNiTi18-10

2013 ◽  
Vol 837 ◽  
pp. 28-32
Author(s):  
Ovidiu Blăjină ◽  
Aurelian Vlase ◽  
Vlad Darie
Keyword(s):  
Stainless Steel ◽  
Tool Life ◽  
Stainless Steels ◽  
Cutting Tool ◽  
Programming Model ◽  
Cutting Speed ◽  
Maximum Productivity ◽  
Optimum Cutting ◽  
Nonlinear Programming Model ◽  
New Research

The research in the last decade regarding their cutting machinability have highlighted the insufficiency of the data for establishing of the optimum cutting processing conditions and the optimum cutting regime. The purpose of this paper is the optimization of the tool life and the cutting speed at the drilling of the stainless steels in terms of the maximum productivity. A nonlinear programming model to maximize the productivity at the drilling of a stainless steel is developed in this paper. The optimum cutting tool life and the associated cutting tool speed are obtained by solving the proposed mathematical model. The use of this productivity model allows greater accuracy in the prediction of the productivity for the drilling of a certain stainless steel and getting the optimum tool life and the optimum cutting speed for the maximum productivity. The obtained results can be used in production activity, in order to increase the productivity of the stainless steels machining. Finally the paper suggests new research directions for the specialists interested in this field.

A Bi-objective Multi-Product Multi-Constraint EPQ Model in a Stochastic Environment and Partial Shortage

2020 ◽  
Vol 19 (03) ◽  
pp. 567-587
Author(s):  
Seyedeh Sanaz Mirkhorsandi ◽  
Seyed Hamid Reza Pasandideh
Keyword(s):  
Goal Attainment ◽  
Programming Model ◽  
Multi Objective ◽  
Holding Costs ◽  
Inventory Costs ◽  
Economic Production ◽  
Proposed Model ◽  
Demand Rate ◽  
Nonlinear Programming Model ◽  
Epq Model

One of the classical models for inventory control is economic production quantity (EPQ), which is widely used in industry. In this paper, an EPQ model with partial shortage is developed by considering the real world conditions, and costs related to the backorder demand are taken as fixed and time-dependent. In the proposed model, determination of the inventory cycle length, the length of positive inventory cycle and backordered demand rate are considered in shortage period. The aim of the presented research is to minimize the total inventory costs and the space required for storage products so that the stochastic and classic constraints including holding costs, lost sales, backorder, budget, total number of productions and average shortage times should be satisfied while optimizing the multi-objective problem. Presented model is a bi-objective nonlinear programming model. Then, to solve the proposed model, three multi-objective decision-making methods including Lp-metric, goal programming and goal attainment are used. Besides, numerical examples are executed in small, medium and large scales by use of GAMS software, and the performance of the methods is compared in terms of objective functions and required CPU time. Finally, sensitivity analysis is done to determine the effect of change in the main parameters of the model on the objective function value.

scholarly journals A Refueling Scheme Optimization Model for the Voyage Charter with Fuel Price Fluctuation and Ship Deployment Consideration

2017 ◽  
Vol 5 (3) ◽  
pp. 267-278 ◽  
Author(s):  
Peng Jia ◽  
Weilun Zhang ◽  
E Wenhao ◽  
Xueshan Sun
Keyword(s):  
Programming Model ◽  
Optimal Solution ◽  
Arma Model ◽  
Maritime Transportation ◽  
Mixed Integer ◽  
Fuel Price ◽  
Shipping Company ◽  
Significant Difference ◽  
Nonlinear Programming Model ◽  
Operation Cycle

Abstract Due to the long operation cycle of maritime transportation and frequent fluctuations of the bunker fuel price, the refueling expenditure of a chartered ship at different time or ports of call make significant difference. From the perspective of shipping company, an optimal set of refueling schemes for a ship fleet operating on different voyage charter routes is an important decision. To address this issue, this paper presents an approach to optimize the refueling scheme and the ship deployment simultaneously with considering the trend of fuel price fluctuations. Firstly, an ARMA model is applied to forecast a time serials of the fuel prices. Then a mixed-integer nonlinear programming model is proposed to maximize total operating profit of the shipping company. Finally, a case study on a charter company with three bulk carriers and three voyage charter routes is conducted. The results show that the optimal solution saves the cost of 437,900 USD compared with the traditional refueling scheme, and verify the rationality and validity of the model.

Sign in / Sign up

Export Citation Format

Share Document