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Energy conservation practices participant manual: For public housing residents and renters
No full textThis training manual focuses on actions which residents can take to improve energy conservation in their homes. (BCS
Exploiting Group Symmetry in Semidefinite Programming Relaxations of the Quadratic Assignment Problem
No full textWe consider semidefinite programming relaxations of the quadratic assignment problem, and show how to exploit group symmetry in the problem data. Thus we are able to compute the best known lower bounds for several instances of quadratic assignment problems from the problem library: [R.E. Burkard, S.E. Karisch, F. Rendl. QAPLIB — a quadratic assignment problem library. Journal on Global Optimization, 10: 291–403, 1997]. AMS classification: 90C22, 20Cxx, 70-08.quadratic assignment problem;semidefinite programming;group sym- metry
Assignment Situations with Multiple Ownership and their Games
No full textAn assignment situation can be considered as a two-sided market consisting of two disjoint sets of objects.A non-negative reward matrix describes the profit if an object of one group is assigned to an object of the other group. Assuming that each object is owned by a different agent, Shapley and Shubik (1972) introduced a class of assignment games arising from these assignment situations.This paper introduces assignment situations with multiple ownership. In these situations each object can be owned by several agents and each agent can participate in the ownership of more than one object.In this paper we study simple assignment games and relaxations that arise from assignment situations with multiple ownership.First, necessary and sufficient conditions are provided for balanced assignment situations with multiple ownership.An assignment situation with multiple ownership is balanced if for any choice of the reward matrix the corresponding simple assignment game is balanced.Second, balancedness results are obtained for relaxations of simple assignment games.assignment situations;matchings;assignment games;balancedness
French 123 Assignment: Group Project
No full textThis assignment is a way to engage with the real world through the practice of French in various areas of everyday life, in order to improve oral and written language skills
Final Assignment - Group Performance
No full textThe final assignment invites students to collaboratively devise and perform a site-specific, immersive theatrical experience in the ground floor of the Music Library. Working in groups, students will create a 7-minute mini-scene that engages with the space, considers audience sensory and emotional experience, and draws on techniques from twentieth-century avant-garde movements as well as insights from their midterm fieldwork. Through workshops, rehearsals, and a public performance, students practice creative collaboration, spatial analysis, and experiential design. The project emphasizes process, responsibility, and teamwork, enabling students to apply course concepts in embodied ways while developing practical skills in directing, performing, and devising. A final Q&A invites reflection on how historical theatrical innovations can inform contemporary site-responsive performance-making
Integrating the fleet assignment model with uncertain demand
No full textThis thesis was submitted for the degree of Master of Philosophy and awarded by Brunel University.One of the main challenges facing the airline industry is planning under uncertainty, especially in the context of schedule disruptions. The robust models and solution algorithms that have been proposed and developed to handle the uncertain parameters will be discussed. Fleet assignment models (FAM) are used by many airlines to assign aircraft to fights in a schedule to maximize profit. In the context of FAM, the goal of robustness is to produce solutions that perform well relative to uncertainties in demand and operation. In this thesis, we introduce new FAMs (i.e. DFAM1 and DFAM2) that tackles the common problem associated with aircraft utilization. Subsequently, stochastic programming (SP) is presented as a method of choice for the research. Through the use of a two-stage SP with recourse technique, the DFAMs are extended to SP-FAMs (SP-FAM1 and SP-FAM2). The main distinction of the SP-FAM compared with other FAMs is that, given a stochastic passenger demand, it gives a strategic fleet assignment solution that hedges against all possible tactical solutions. In addition, we have a tactical solution for every scenario. In generating the demand scenarios, we use a network-simulation model embedded with a time-series engine that gives a snapshot of one week that is representative of any other week of the scheduling season. We later outline the approach of solving the SP-FAMs where the schedule is compacted through several preprocessing steps before inputting it into SAS-AMPL converter. The SAS-AMPL converter prepares all the data into readable AMPL format. Finally, we execute the optimizer using a FortMP solver (integrated in AMPL) that invokes branch-and-bound algorithm. We give a proof of concept using real data from a Middle East airline. Our investigations establish clear benefits of the recourse FAM compared to alternative models. Finally, we propose areas of future research to improve SP-FAM robustness through solution algorithms, revenue management (RM) effects, calibration of network-simulation models and system integration
Cue competition affects temporal dynamics of edge-assignment in human visual cortex
No full textEdge-assignment determines the perception of relative depth across an edge and the shape of the closer side. Many cues determine edge-assignment, but relatively little is known about the neural mechanisms involved in combining these cues. Here, we manipulated extremal edge and attention cues to bias edge-assignment such that these two cues either cooperated or competed. To index their neural representations, we flickered figure and ground regions at different frequencies and measured the corresponding steady-state visual-evoked potentials (SSVEPs). Figural regions had stronger SSVEP responses than ground regions, independent of whether they were attended or unattended. In addition, competition and cooperation between the two edge-assignment cues significantly affected the temporal dynamics of edge-assignment processes. The figural SSVEP response peaked earlier when the cues causing it cooperated than when they competed, but sustained edge-assignment effects were equivalent for cooperating and competing cues, consistent with a winner-take-all outcome. These results provide physiological evidence that figure-ground organization involves competitive processes that can affect the latency of figural assignment
System optimal traffic assignment with departure time choice
No full textThis thesis investigates analytical dynamic system optimal assignment with departure time
choice in a rigorous and original way. Dynamic system optimal assignment is formulated here
as a state-dependent optimal control problem. A fixed volume of traffic is assigned to
departure times and routes such that the total system travel cost is minimized. Although the
system optimal assignment is not a realistic representation of traffic, it provides a bound on
performance and shows how the transport planner or engineer can make the best use of the
road system, and as such it is a useful benchmark for evaluating various transport policy
measures. The analysis shows that to operate the transport system optimally, each traveller in
the system should consider the dynamic externality that he or she imposes on the system from
the time of his or her entry. To capture this dynamic externality, we develop a novel
sensitivity analysis of travel cost. Solution algorithms are developed to calculate the dynamic
externality and traffic assignments based on the analyses. We also investigate alternative
solution strategies and the effect of time discretization on the quality of calculated
assignments. Numerical examples are given and the characteristics of the results are discussed.
Calculating dynamic system optimal assignment and the associated optimal toll could be too
difficult for practical implementation. We therefore consider some practical tolling strategies
for dynamic management of network traffic. The tolling strategies considered in this thesis
include both uniform and congestion-based tolling strategies, which are compared with the
dynamic system optimal toll so that their performance can be evaluated. In deriving the
tolling strategies, it is assumed that we have an exact model for the underlying traffic
behaviour. In reality, we do not have such information so that the robustness of a toll
calculation method is an important issue to be investigated in practice. It is found that the
tolls calculated by using divided linear traffic models can perform well over a wide range of
scenarios. The divided linear travel time models thus should receive more attention in the
future research on robust dynamic traffic control strategies design. In conclusion, this thesis
contributes to the literature on dynamic traffic modelling and management, and to support
further analysis and model development in this area
Maximally Flexible Assignment of Orthogonal Variable Spreading Factor Codes for Multi-Rate Traffic
No full textIn universal terrestrial radio access (UTRA) systems, orthogonal variable spreading factor (OVSF) codes are used to support different transmission rates for different users. In this paper, we first define the flexibility index to measure the capability of an assignable code set in supporting multirate traffic classes. Based on this index, two single-code assignment schemes, nonrearrangeable and rearrangeable compact assignments, are proposed. Both schemes can offer maximal flexibility for the resulting code tree after each code assignment. We then present an analytical model and derive the call blocking probability, system throughput and fairness index. Analytical and simulation results show that the proposed schemes are efficient, stable and fair
A Lagrangian discretization multiagent approach for large-scale multimodal dynamic assignment
No full textThis paper develops a Lagrangian discretization multiagent model for large-scale multimodal simulation and assignment. For road traffic flow modeling, we describe the dynamics of vehicle packets based on a macroscopic model on the basis of a Lagrangian discretization. The metro/tram/train systems are modeled on constant speed on scheduled timetable/frequency over lines of operations. Congestion is modeled as waiting time at stations plus induced discomfort when the capacity of vehicle is achieved. For the bus system, it is modeled similar to cars with different speed settings, either competing for road capacity resources with other vehicles or moving on separated bus lines on the road network. For solving the large-scale multimodal dynamic traffic assignment problem, an effective-path-based cross entropy is proposed to approximate the dynamic user equilibrium. Some numerical simulations have been conducted to demonstrate its ability to describe traffic dynamics on road network.multimodal transportation systems; Lagrangian discretization; traffic assignment; multiagent systems
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