An inexact optimization model for evacuation planning

Abstract

Purpose -The purpose of this paper is to develop an interval method for vehicle allocation and route planning in case of an evacuation. Design/methodology/approach -First, the evacuation route planning system is described and the notations are defined. An inexact programming model is proposed. The goal of the model is to achieve optimal planning of vehicles allocation with a minimized system time under the condition of inexact information. The constraints of the model include four types: number of vehicles constraint, passengers balance constraints, maximum capacity of links constraints and no negative constraints. The model is solved through the decomposition of the inexact model. A hypothetical case is developed to illustrate the proposed model. Findings -The paper finds that the interval solutions are feasible and stable for evacuation model in the given decision space, and this may reduce the negative effects of uncertainty, thereby improving evacuation managers' estimates under different conditions. Originality/value -This method entails incorporation of uncertainties existing as interval values into model formulation and solution procedure, and application of the developed model and the related solution algorithm in a hypothetical case study.

A Fuzzy Evacuation Management Model Oriented Toward the Mitigation of Emissions

“…The above characteristics distinguish event-related evacuation processes from emergency-induced ones. Scientific planning for routing strategies and vehicle allocation is the major concern, which primarily relies on efficient utilization of transportation resources and services (Chiu et al, 2007;Wu et al, 2009). Recent advancements in sensor technologies have facilitated the acquisition of a wide range of traffic information, from tracking vehicles presence, volume and speed, to detecting vehicle density or travel time (Hamza-Lup et al, 2005).…”

“…(ii) CO is high toxic, posing serious threats to human health and the environment (Kongtip et al, 2006;Gokhale and Khare 2007). Thus, CO has been frequently used as a predominant indicator of pollutant emissions in many transportation-related studies (Read, 1994;Wu et al, 2009). The related emission standards for CO can be obtained from the regulations of municipal authorities.…”

“…The study network consists of one origin, three destinations (D1 to D3), two traffic lights (Lt1 and Lt2), one toll station (T1), and eight links connecting the nodes (L1 to L8) (Wu et al, 2009). The evacuation planners are responsible for evacuating the event participants through public transit from the evacuation origin to the three destinations scattered in a city.…”

Fire evacuation model with confidence intervals

“…The concept of interval linear programming is introduced to address uncertain problems for evacuation [2]. Uncertainties are expressed as interval numbers in the optimization process.…”

TISEM: A Two-Stage Interval-Stochastic Evacuation Management Model

“…Therefore, time is usually considered top priority during evacuation processes (Urbanik, 2000;Yi and Zdamar, 2007). At the same time, a series of issues such as economic costs, contaminant emissions and traffic interferences should also be taken into consideration when the evacuation time is to be minimized (Graata et al, 1999;Wu et al, 2008;Tan et al, 2008). Thus, systems analysis techniques could be employed to assist in developing evacuation management plans, which may be helpful for making tradeoffs between meeting required environmental objectives and minimizing system cost.…”