A mixed-integer linear programming approach to the optimization of event-bus schedules: a scheduling application in the tourism sector

This paper deals with “The Enchanted Journey,” which is a daily event tour booked by Bollywood-film fans. During the tour, the participants visit original sites of famous Bollywood films at various locations in Switzerland; moreover, the tour includes stops for lunch and shopping. Each day, up to five buses operate the tour. For operational reasons, however, two or more buses cannot stay at the same location simultaneously. Further operative constraints include time windows for all activities and precedence constraints between some activities. The planning problem is how to compute a feasible schedule for each bus. We implement a two-step hierarchical approach. In the first step, we minimize the total waiting time; in the second step, we minimize the total travel time of all buses. We present a basic formulation of this problem as a mixed-integer linear program. We enhance this basic formulation by symmetry-breaking constraints, which reduces the search space without loss of generality. We report on computational results obtained with the Gurobi Solver. Our numerical results show that all relevant problem instances can be solved using the basic formulation within reasonable CPU time, and that the symmetry-breaking constraints reduce that CPU time considerably.

A dynamic programming approach to the formulation and solution of finite element equations

A method for formulating and algorithmically solving the equations of finite element problems is presented. The method starts with a parametric partition of the domain in juxtaposed strips that permits sweeping the whole region by a sequential addition (or removal) of adjacent strips. The solution of the difference equations constructed over that grid proceeds along with the addition removal of strips in a manner resembling the transfer matrix approach, except that different rules of composition that lead to numerically stable algorithms are used for the stiffness matrices of the strips. Dynamic programming and invariant imbedding ideas underlie the construction of such rules of composition. Among other features of interest, the present methodology provides to some extent the analyst's control over the type and quantity of data to be computed. In particular, the one-sweep method presented in Section 9, with no apparent counterpart in standard methods, appears to be very efficient insofar as time and storage is concerned. The paper ends with the presentation of a numerical example

Finding relevant search engine results:a minimax linear programming approach

For a submitted query to multiple search engines finding relevant results is an important task. This paper formulates the problem of aggregation and ranking of multiple search engines results in the form of a minimax linear programming model. Besides the novel application, this study detects the most relevant information among a return set of ranked lists of documents retrieved by distinct search engines. Furthermore, two numerical examples aree used to illustrate the usefulness of the proposed approach.

Evaluation of public housing strategies in Mexico City : an exploratory goal programming approach

This thesis describes the development and use of a goal programming methodology for the evaluation of public housjng strategies in Mexico City, The methodology responds to the need to incorporate the location, size and densities of housing projects on the one hand, and "external" constraints such as the ability of low income families to pay for housing, and the amounts of capital and land available, on the other. The provision of low cost housing by public housing agencies in Mexico City is becoming increasingly difficult because there are so many constraints to be met and overcome, the most important of which is the ability of families to pay for housing. Other important limiting factors are the availability of capital and of land plots of the right size in desired locations. The location of public housing projects is significant because it determines the cost and pattern of work trips, which in a metropolitan area such as Mexico City are of considerable importance to both planners and potential. house owners. In addition, since the price of land is closely related to its location, the last factor is also significant in determining the price of the total housing package. Consequently there is a major trade-off between a housing strategy based on the provision of housing at locations close to employment, and the opposite one based on the provjsion of housjng at locations where employment accessibility is poorer but housing can be provided at a lower price. The goal programming evaluation methodology presented in this thesis was developed to aid housing planners to evaluate housing strategies which incorporate the issues raised above,

Integer Programming Approach to HP Folding

One of the most widely studied protein structure prediction models is the hydrophobic-hydrophilic (HP) model, which explains the hydrophobic interaction and tries to maximize the number of contacts among hydrophobic amino-acids. In order to find a lower bound for the number of contacts, a number of heuristics have been proposed, but finding the optimal solution is still a challenge. In this research, we focus on creating a new integer programming model which is capable to provide tractable input for mixed-integer programming solvers, is general enough and allows relaxation with provable good upper bounds. Computational experiments using benchmark problems show that our formulation achieves these goals.

Assisting decision-making in Queensland barley production through chance constrained programming

A chance constrained programming model is developed to assist Queensland barley growers make varietal and agronomic decisions in the face of changing product demands and volatile production conditions. Unsuitable or overlooked in many risk programming applications, the chance constrained programming approach nonetheless aptly captures the single-stage decision problem faced by barley growers of whether to plant lower-yielding but potentially higher-priced malting varieties, given a particular expectation of meeting malting grade standards. Different expectations greatly affect the optimal mix of malting and feed barley activities. The analysis highlights the suitability of chance constrained programming to this specific class of farm decision problem.

Integer Programming on Domains Containing Inseparable Ordered Paris

Using the integer programming approach introduced by Sethuraman, Teo, and Vohra (2003), we extend the analysis of the preference domains containing an inseparable ordered pair, initiated by Kalai and Ritz (1978). We show that these domains admit not only Arrovian social welfare functions \without ties," but also Arrovian social welfare functions \with ties," since they satisfy the strictly decomposability condition introduced by Busetto, Codognato, and Tonin (2012). Moreover, we go further in the comparison between Kalai and Ritz (1978)'s inseparability and Arrow (1963)'s single-peak restrictions, showing that the former condition is more \respectable," in the sense of Muller and Satterthwaite (1985).

Comparison of Work Scheduling Using Constraint Programming or Auctions

Business processes designers take into account the resources that the processes would need, but, due to the variable cost of certain parameters (like energy) or other circumstances, this scheduling must be done when business process enactment. In this report we formalize the energy aware resource cost, including time and usage dependent rates. We also present a constraint programming approach and an auction-based approach to solve the mentioned problem including a comparison of them and a comparison of the proposed algorithms for solving them