Recent advances in location analysis

The final publication is available at Elsevier via http://dx.doi.org/10.1016/j.cor.2015.04.013 © 2015. This manuscript version is made available under the CC-BY-NC-ND 4.0 license http://creativecommons.org/licenses/by-nc-nd/4.0/Introduction to a special issue of Computers & Operations Research dedicated to recent advances in location analysis

Recent advances in location analysis

[No abstract available

Geographic concentration of economic activities: on the validation of a distance-based mathematical index to identify optimal locations

The present study proposes a validation of a mathematical index Q able to identify optimal geographic places for economic activities, solely based on the location variable. This research work takes its roots in the 1970s with the statistical analysis of spatial patterns, or analysis of point processes, whose main goal is to understand if a resulting spatial distribution of points is due to chance or not. Indeed point objects are commonplace (towns in regions, plants in the landscape, galaxies in space, shops in towns) and the development of specific mathematical tools are useful to understand their own location processes. Spatial point deviations from purely random configurations may be analyzed either by quadrat or by distance methods. An interesting method of the second category – the cumulative function M – was developed recently for evaluating the relative geographic concentration and co-location of industries in a nonhomogeneous spatial framework. On this basis, and having quantified retail store interactions, The French physicist Pablo Jensen elaborated the Q-index to automatically detect promising locations. To test the relevance of this quality index, Jensen used location data from 2003 and 2005 for bakeries in the city of Lyon and discovered that between these two years, shops having closed were located on significantly lower quality sites. Here, using bankruptcy data provided by the Registrar of companies of the State of Valais in Switzerland and by the City Council of Glasgow in Scotland, we implemented a method based on univariate logistic regressions to systematically test for the relevance of the Q-index on the many commercial categories available. We show that the Q-index is reliable, although significance tests did not reach stringent levels. Access to trustable bankruptcy data remains a difficult task

Time-dependent stochastic methods for managing and scheduling Emergency Medical Services

Emergency Medical Services (EMS) are facing increasing pressures in many nations given that demands on the service are rising. This article focuses in particular on the operations of the Welsh Ambulance Service Trust (WAST), which is the only organisation that provides urgent paramedical care services on a day-to-day basis across the whole of Wales. In response to WAST’s aspiration to improve the quality of care it provides, this research investigates several interrelated advanced statistical and operational research (OR) methods, culminating in a suite of decision support tools to aid WAST with capacity planning issues. The developed techniques are integrated in a master workforce capacity planning tool that may be independently operated by WAST planners. By means of incorporating methods that seek to simultaneously better predict future demands, recommend minimum staffing requirements and generate low-cost rosters, the tool ultimately provides planners with an analytical base to effectively deploy resources. Whilst the tool is primarily developed for WAST, the generic nature of the methods considered means they could equally be applied to any service subject to demand that is of an urgent nature, cannot be backlogged, is heavily time-dependent and highly variabl

Integrated Forward and Reverse Logistics Network Design

Many manufacturers are moving towards green manufacturing. One of the actions for environment friendly manufacturing is collection of end-of-life products (EOL). EOL products are transported to the proper facilities for reprocessing or proper disposal. Movement of collected products is performed through reverse logistics networks. Reverse logistics networks may be designed independent of forward logistics networks, or as integrated networks, known as integrated forward and reverse logistics (IFRL) networks. Recent research shows that IFRL networks are more efficient than independent networks. In this work, we study a number of IFRL networks. We present a comprehensive mathematical model to represent an assignment and location-routing IFRL network. Afterwards, this model is decomposed into a number of sub-models that represent different IFRL networks. For each network we develop a solution methodology to solve practical size problems. Two sub-models based on the comprehensive model are presented to design two IFRL location-routing networks. The first network considers decision on the location to establish a disassembly plant. The second network considers decisions on the location to establish a manufacturing facility. For both networks, routing decisions are assigning customers to vehicles, and establishing vehicles’ routes. We develop two heuristic methods to solve the models. The heuristics are able to reach optimal or near optimal solutions in reasonable computational times. The vehicle routing problem with simultaneous pickup and delivery and time windows (VRPSPD-TW) is studied in this work. We use a sub-model of the comprehensive model to represent the problem. Classic heuristics and intelligent optimization or metaheuristics are widely used to solve similar problems. Therefore, we develop a heuristic method to solve the VRPSPD-TW. Results of the heuristic serve as initial solutions for a simulated annealing (SA) approach. For most tested problems, the SA approach is able to improve the heuristic solutions, and reach optimal solutions. Computational times are reasonable for the heuristic and SA. We also study the multi-depot vehicle routing problem with simultaneous pickup and delivery and time windows (MDVRPSPS-TW). A sub-model of the comprehensive model represents the problem. The network considers assignment of customers and vehicles to depots, assignment of customers to vehicles and routing of vehicles within customers’ time windows. We develop a 2-phase heuristic and a SA approach to solve the problem. Heuristic solutions serve as initial solutions for the SA approach. SA is able to reach optimum or near optimum solutions. Computational times are reasonable for the heuristic and S

Concept demonstrator: Holding site location, ambulance allocation, and relocation decision support tool

Thesis (MEng)--Stellenbosch University, 2017.ENGLISH ABSTRACT: Before the start of a shift, the dispatchers at the Western Cape Emergency Control Centre (WC ECC) decide where to place holding sites and how many ambulance to allocate to each holding site. During a shift they decide when and where to relocate ambulances. At present, dispatchers make these decisions based solely on their experience and intuition. In this project a concept demonstrator decision support tool (DST) is developed which produces solutions for the near-optimal placement of holding sites per shift, ambulance allocation, and relocation per hour of that shift based on predicted ambulance demand rates. The DST is developed with the aim of assisting the dispatchers at the WC ECC with holding site placement, ambulance allocation, and relocation decisions. The real-world instance utilised during the development of the concept demonstrator DST consists of six months' historical call data from the City of Cape Town and the Cape Winelands municipalities. Singular spectrum analysis is used to forecast ambulance demand according to incident priority. The extended queuing maximum availability location problem model is adapted to t the real-world instance. The model aims to simultaneously maximise expected ambulance coverage and minimise ambulance relocations by manipulating holding site placement, ambulance allocation, and relocation. The solution method implemented for the model as a whole is the arti cial bee colony algorithm. The DST was solved for four planning week instances, at 95% service reliability. Predicted demand for the planning week is predicted using historical demand that precedes the planning week and a recommended schedule of holding site placement, ambulance allocation, and relocation is generated for the predicted ambulance demand. The performance of this schedule is evaluated using the observed historical demand for the planning week. Di erent approaches for the classi cation of calls { consider all calls to be life-threatening, or calls to be life-threatening or non-life-threatening { as well as for the implementation of the model constraints are considered. The results indicate that the WC ECC can improve ambulance coverage with the current, or even smaller, ambulance eet size if decisions are made with the assistance of the DST that anticipates the probable future ambulance demand. The concept demonstrator DST's solutions' expected percentage coverage compared to the actual percentage coverage exceeds 150%. However, it is invalid to compare these values like-for-like as a signi cant number of real-world factors, including the speci c road conditions at the time of each call, the responsiveness of both the ECC operator handling the call and the ambulance team involved, and the communication connection between the ECC call operator and the ambulance team, in uence the real-world response rate and could not be modelled in the DST. However, even when these factors are taken into account, the discrepancy between the actual and the predicted performance is sufficient to convincingly demonstrate the potential of the concept demonstrator DST to assist theWC ECC in further improving their response time.AFRIKAANSE OPSOMMING: Voor die aanvang van 'n skof besluit die ambulaansversenders by die Wes- Kaapse noodbeheersentrum (WC ECC) waar om wagstasies te plaas en hoeveel ambulanse om by elkeen te plaas. Tydens 'n skof besluit hulle wanneer en waarheen ambulanse geskuif moet word. Tans, maak die versenders staat slegs op hul eie ervaring en intu sie om hul besluitneming te lei. In die projek is 'n konsep demonstreerder besluitsteunstelsel (DST) gebou wat oplossings vir die naas-optimale plasing van wagstasies per skof, ambulaansplasing en -rondskuiwing per uur van daardie skof bepaal gebaseer op voorspelde ambulaansaanvraag. Die konsep demonstreerder DST is ontwikkel met die doel om die versenders by die WC ECC te help met die besluitneming aangaande wagstasieplasing, ambulaansplasing en -rondskuiwing. Die werklikheidsgeval, waarvoor die DST ontwikkel word, bestaan uit ses maande se historiese oproepdata van die Stad Kaapstad en die Kaapse Wynland munisipaliteite. `Singular spectrum analysis' is gebruik om die ambulaansaanvraag volgens voorvalprioriteit te voorspel. Die uitgebreide `queuing maximum availability location problem' model is aangepas om by die werklikheidsgeval te pas. Die model streef om die maksimum verwagte ambulaansdekking en die minimum rondskuiwingskoste deur middel van verbeterde wagstasieplasing, ambulaansplasing en -rondskuiwing te vind. Die oplossingsmetode wat gebruik is vir die algehele model is die `arti cial bee colony' algoritme. Die DST is vir vier gevalle opgelos met 'n 95% diensbetroubaarheidsvlak. Die ambulaansaanvraag vir die beplanningsweek is voorspel gebaseer op historiese ambulaansaanvraag, wat nie die beplanningsweek se historiese ambulaansaanvraag bevat nie. Daarna is'n aanbevole wagstasieplasing, ambulaansplasing en -rondskuiwing skedule gegenereer vir die voorspelde ambulaansaanvraag. Die skedule is geïmplimenteer vir die beplanningsweek. se historiese ambulaans aanvraag. Die resultate is gebruik om die skedule se prestasie the evalueer. Verskillende benaderings vir die hantering van die oproepe volgens voorvalprioriteit { ag alle oproepe as lewensbedreigend, of ag hulle as lewensbedreigend of nie-lewensbedreigend { en twee implementerings van die ambulaansplasingsbeperking word oorweeg. Die resultate dui aan dat die WC ECC die ambulaansdekking kan verbeter met die huidige, of selfs kleiner, ambulaansvloot as besluite geneem word met behulp van die konsep demonstreerder DST in afwagting van die waarskynlike ambulaansaanvraag. Die DST se oplossings se verwagte persentasie ambulaansdekking oorskry die werklike persentasie ambulaansdekking wat bepaal is vir die historiese oproepdata met 150%. Dit moet inaggeneem word dat hierdie waardes nie dieselfde is nie. Beduidende gevalle van die werklikheidsgeval se faktore, insluitend die spesi eke toestand van die paaie tydens elke oproep, die uksheid van die noodbeheersentrum se telefoonoperateur en die ambulaansbemanning, en die kommunikasie tussen die telefoonoperateur en die ambulaansbemanning, be nvloed die werklike reaksietyd en kon nie gemodelleer word nie. Tog, selfs wanneer die faktore inaggeneem word, is die verskil tussen die waargenome en voorspelde prestasies voldoende om oortuigend die potensiaal van die konsep demonstreerder DST te demonstreer as hulpmiddel vir die WC ECC om hul reaksietye verder te verbeter

Time-dependent stochastic modelling for predicting demand and scheduling of emergency medical services

As the prominence of the service sector is increasing in developed nations, new and exciting opportunities are arising for operational researchers to develop and apply models which offer managers solutions to improve the quality of their services. The development of time-dependent stochastic models to analyse complex service systems and generate effective personnel schedules are key to this process, enabling organisations to strike a balance between the provision of a good quality service whilst avoiding unnecessary personnel costs. Specifically within the healthcare sector, there is a need to promote efficient management of an Emergency Medical Service (EMS), where the probability of survival is directly related to the speed of assistance. Motivated by case studies investigating the operation of the Welsh Ambulance Service Trust (WAST), this thesis aims to investigate how operational research (OR) techniques can be developed to analyse priority service systems subject to demand that is of an urgent nature, cannot be backlogged, is heavily time-dependent and highly variable. A workforce capacity planning tool is ultimately developed that integrates a combination of forecasting, queueing theory, stochastic modelling and optimisation techniques into a single spreadsheet model in order to predict future demand upon WAST, set staffing levels, and optimise shift schedules and rosters. The unique linking together of the techniques in a planning tool which further captures time-dependency and two priority classes enables this research to outperform previous approaches, which have generally only considered a single class of customer, or generated staffing recommendations using approximation methods that are only reliable under limited conditions. The research presented in this thesis is novel in several ways. Primarily, the first section considers the potential of a nonparametric modelling technique known as Singular Spectrum Analysis (SSA) to improve the accuracy of demand forecasts. Secondly, the main body of work is dedicated to adapting numerical queueing theory techniques to accurately model the behaviour of time-dependent multi-server priority systems across shift boundaries and evaluate the likelihood of excessive waits for service for two customer classes. The final section addresses how shifts can be optimally scheduled using heuristic search techniques. The main conclusions are that in addition to offering a more flexible approach, the forecasts generated by SSA compare favourably to those obtained using traditional methods, and both approximate and numerical modelling techniques may be duly extended to set staffing levels in complex priority systems

Modelling Emergency Medical Services

Emergency Medical Services (EMS) play a pivotal role in any healthcare organisation. Response and turnaround time targets are always of great concern for the Welsh Ambulance NHS Trust (WAST). In particular, the more rural areas in South East Wales consistently perform poorly with respect to Government set response standards, whilst delayed transfer of care to Emergency Departments (EDs) is a problem publicised extensively in recent years. Many Trusts, including WAST, are additionally moving towards clinical outcome based performance measures, allowing an alternative system-evaluation approach to the traditional response threshold led strategies, resulting in a more patient centred system. Three main investigative parts form this thesis, culminating in a suite of operational and strategic decision support tools to aid EMS managers. Firstly, four novel allocation model methods are developed to provide vehicle allocations to existing stations whilst maximising patient survival. A detailed simulation model then evaluates clinical outcomes given a survival based (compared to response target based) allocation, determining also the impact of the fleet, its location and a variety of system changes of interest to WAST (through ‘what-if?’ style experimentation) on entire system performance. Additionally, a developed travel time matrix generator tool, enabling the calculation and/or prediction of journey times between all pairs of locations from route distances is utilised within the aforementioned models. The conclusions of the experimentation and investigative processes suggest system improvements can in fact come from better allocating vehicles across the region, by reducing turnaround times at hospital facilities and, in application to South East Wales, through alternative operational policies without the need to increase resources. As an example, a comparable degree of improvement in patient survival is witnessed for a simulation scenario where the fleet capacity is increased by 10% in contrast to a scenario in which ideal turnaround times (within the target) occur