A new formulation and heuristics for some vehicle scheduling problems on a time-space network

One of the problems in public transportation is the vehicle scheduling problem (VSP), which can reduce the bus company cost and meet the demand of passengers’ minimum waiting time. This paper proposes an ensemble differential algorithm based on particle swarm optimization (abbreviated as PSOEDE) to solve the VSP. In PSOEDE algorithm, the mutation process is designed by dividing the original process into two parts: the first part combines the PSO operator with the improved mutation strategy to enhance the global search ability, while the second part is to randomly select two mutation strategies (i.e. random learning and optimal learning) to improve the diversity of population. In addition, the random selection methods of the parameters and crossover strategies are proposed and applied in the total PSOEDE algorithm. The effectiveness and superiority of the proposed PSOEDE algorithm in dealing with the VSP are verified using the simulation experiments and six comparison algorithms.

Decomposition based approaches are recalled from primal and dual point of view. The possibility of building partially disaggregated reduced master problems is investigated. This extends the idea of aggregated-versus-disaggregated formulation to a gradual choice of alternative level of aggregation. Partial aggregation is applied to the linear multicommodity minimum cost flow problem. The possibility of having only partially aggregated bundles opens a wide range of alternatives with different trade-offs between the number of iterations and the required computation for solving it. This trade-off is explored for several sets of instances and the results are compared with the ones obtained by directly solving the natural node-arc formulation. An iterative solution process to the route assignment problem is proposed, based on the well-known Frank Wolfe algorithm. In order to provide a first feasible solution to the Frank Wolfe algorithm, a linear multicommodity min-cost flow problem is solved to optimality by using the decomposition techniques mentioned above. Solutions of this problem are useful for network orientation and design, especially in relation with public transportation systems as the Personal Rapid Transit. A single-commodity robust network design problem is addressed. In this, an undirected graph with edge costs is given together with a discrete set of balance matrices, representing different supply/demand scenarios. The goal is to determine the minimum cost installation of capacities on the edges such that the flow exchange is feasible for every scenario. A set of new instances that are computationally hard for the natural flow formulation are solved by means of a new heuristic algorithm. Finally, an efficient decomposition-based heuristic approach for a large scale stochastic unit commitment problem is presented. The addressed real-world stochastic problem employs at its core a deterministic unit commitment planning model developed by the California Independent System Operator (ISO).

An efficient assignment and scheduling of tasks of a multiprocessor program is one of the key elements in the effective utilization of multiprocessor systems. This problem being hard to solve exactly, is the reason that so many heuristic methods for finding a suboptimal schedule exist (Hou et al., 1994; Tsuchiya et al., 1997). This paper addresses the problem of multiprocessor scheduling represented as a directed acyclic task graph (DAG) without communication costs to fully connected multiprocessors. We proposed an algorithm, called PGA/SPF (Priority-based Genetic Algorithm/Shortest Processor First schedule) where a priority-based genetic algorithm is improved with the introduction of some knowledge about the scheduling problem, which is represented by the use of genetic operators as crossover and mutation operators. And, a new mapping method, shortest processor first schedule, assigns the selected task to a processor that can minimize a task execution time efficiently. The proposed algorithms generate similar or even better solutions than the previous algorithms in terms of the completion times of the resulting schedules.

This thesis explores possibilities and limitations of extending classical combinatorial optimization problems for network flows and network design. We propose new mathematical models for logistics networks that feature commodities with multidimensional properties, e.g. their mass and volume, to capture consolidation effects of commodities with complementing properties. We provide new theoretical insights and solution methods with immediate practical impact that we test on real-world instances from the automotive, chemical, and retail industry. The first model is for tactical transportation planning with temporal consolidation effects. We propose various heuristics and prove for our instances, that most of our solutions are within a single-digit percentage of the optimum. We also study problem variants where commodities are routed unsplittably and give hardness results for various special cases and a dynamic program that finds optimal forest solutions, which overestimate real costs. The second model is for strategic route planning under uncertainty. We provide for a robust optimization method that anticipates fluctuations of demands by minimizing worst-case costs over a restricted scenario set. We show that the adversary problem is NP-hard. To still find solutions with very good worst-case cost, we derive a carefully relaxed and simplified MILP, which solves well for large instances. It can be extended to include hub decisions leading to a robust M-median hub location problem. We find a price of robustness for our instances that is moderate for scenarios using average demand values as lower bounds. Trend based scenarios show a considerable tradeoff between historical average costs and worst case costs. Another robustness concept are incremental hub chains that provide solutions for every number of hubs to operate, such that they are robust under changes of this number. A comparison of incremental solutions with M-median solutions obtained with an LP-based search suggests that a price of being incremental is low for our instances. Finally, we investigate the problem of scheduling the maintenance of edges in a network. We focus on maintaining connectivity between two nodes over time. We show that the problem can be solved in polynomial time in arbitrary networks if preemption is allowed. If preemption is restricted to integral time points, the problem is NP-hard and for the non-preemptive case, we show strong non-approximability results.

This paper examines time windows for scheduled trips in multiple depot vehicle and crew scheduling problems that arise in public bus transportation. In practice, the two planning tasks vehicle scheduling and crew scheduling are traditionally solved sequentially with the implicit understanding that the scheduled time for timetabled trips remains fixed. In order to improve cost efficiency two concepts have been developed over the last years: In order to obtain better flexibility when scheduling crews, vehicle and crew scheduling problems are tackled simultaneously. In order to extend flexibility while scheduling vehicles, variable trip departure and arrival times are considered. Obviously the combination of both concepts promises the largest savings, but probably leads to bursting computational times due to growing problem complexity. In this paper we combine both concepts by extending the integrated vehicle and crew scheduling problem with the possibility to shift scheduled trips within defined time windows. We examine the tradeoffs between solution quality and computational time for different solution approaches.

The periodic event scheduling problem (PESP) is a well studied problem known as intrinsically hard. Its main application is for designing periodic timetables in public transportation. To this end, the passengers' paths are required as input data. This is a drawback since the final paths which are used by the passengers depend on the timetable to be designed. Including the passengers' routing in the PESP hence improves the quality of the resulting timetables. However, this makes PESP even harder. Formulating the PESP as satisfiability problem and using SAT solvers for its solution has been shown to be a highly promising approach. The goal of this paper is to exploit if SAT solvers can also be used for the problem of integrated timetabling and passenger routing. In our model of the integrated problem we distribute origin-destination (OD) pairs temporally through the network by using time-slices in order to make the resulting model more realistic. We present a formulation of this integrated problem as integer program which we are able to transform to a satisfiability problem. We tested the latter formulation within numerical experiments, which are performed on Germany's long-distance passenger railway network. The computation's analysis in which we compare the integrated approach with the traditional one with fixed passengers' weights, show promising results for future scientific investigations.

Modeling and solving the multimodal car- and ride-sharing problem

Introduction: This study assesses the economic feasibility of implementing electric buses in Juiz de Fora - MG, considering acquisition, operation, and maintenance costs compared to diesel models. The methodology is based on the Total Cost of Ownership (TCO) analysis, considering factors such as charging infrastructure, energy consumption, government incentives, environmental impact, and public policies related to electromobility.The results indicate that, although electric buses present 24% lower maintenance costs and up to 88.9% reduction in electricity expenses when combined with solar energy, the high initial acquisition cost and the need for structural investments compromise their economic feasibility in the short term. Additionally, implementing charging infrastructure represents a significant financial challenge for public transport operators. However, the analysis shows that alternative financing models, such as battery leasing and public-private partnerships (PPPs), can mitigate some of the financial challenges. Furthermore, more robust public policies, such as government subsidies, tax exemptions, and differentiated electricity tariffs, are essential to enable the energy transition in the public transport sector. Thus, this study reinforces the need for economic and regulatory strategies to facilitate fleet electrification, making urban transport more efficient, sustainable, and economically accessible in the long run. Objective: This article aims to analyze the economic feasibility of implementing electric buses in public transport in Juiz de Fora - MG, considering acquisition, operation, and maintenance costs compared to diesel buses. To achieve this, factors such as energy efficiency, charging infrastructure, government incentive policies, and available financing models will be evaluated. Additionally, the study seeks to identify the challenges and opportunities associated with transitioning to an electric fleet in the city, providing subsidies for decision-making by public managers and transport companies. Theoretical Framework: The study highlights the Total Cost of Ownership (TCO) analysis, financing models for electromobility, public policies for sustainable transport, and environmental impacts of fleet electrification, providing a solid foundation for understanding the research context. Method: The methodology adopted in this research follows a quantitative approach, based on Total Cost of Ownership (TCO) analysis and the economic feasibility assessment of fleet electrification. Data was collected from operational cost surveys, energy consumption analysis, and investments in charging infrastructure, supplemented by information from case studies and secondary sources, such as technical reports and industry regulations. Results and Discussion: The results revealed that, despite up to 24% lower maintenance costs and up to 88.9% electricity savings when using solar energy, the high initial cost of electric buses and charging infrastructure compromises their economic feasibility in the short term. In the discussion section, these results are contextualized within the theoretical framework, emphasizing the importance of government subsidies, tax incentives, and alternative financing models to enable fleet electrification. Research Implications: The practical and theoretical implications of this research are discussed, providing insights into how the findings can influence sustainable mobility and electromobility practices. These implications include public policy planning for urban transport, the adoption of financing models for electric fleets, and the feasibility of integrating renewable energy into the sector. Additionally, the findings may contribute to strategies that reduce economic barriers and encourage the transition to a more efficient and sustainable public transport system. Originality/Value: This study contributes to the literature by analyzing the economic feasibility of fleet electrification in a medium-sized city in Brazil, a topic still underexplored in local contexts. The innovative approach includes the integration of solar energy as an alternative to reducing operational costs, expanding the debate on sustainability in public transport. The relevance and value of this research are highlighted by its potential impact on public policy formulation, urban planning, and the adoption of more accessible financial models for energy transition in the mobility sector.

Market research in developed countries is condition sine qua none business of successful companies. On the other hand, market orientation as the key mechanism of allocation of limited economic resources in the countries of transition is still in the implementation phase. This paper deals with the issues of market research in the function of business decisions, on the example of companies in the South Backa region (Republic of Serbia). The many-year transition process (it has been going on for 20 years now), the insufficiently developed market mechanisms, the problems imminent to the nature of transition – monopoles, slow decentralization and non-efficient institutional system resulted in the fact that companies are relatively slow in the implementation of modern business methods. The first part of the paper aims to define market research on theoretical-methodological level. The second part of the paper deals with the influence of research on company businesses, as well as the implementation of the research on company decision-making. The third part of the paper presents certain aspects of market research of companies in the South Backa region. The aim of the research implies the representation of market research analysis as a modern business method. The informative significance that company management attaches to market research results in the context of business decision-making has also been analyzed. The fourth part of the paper is reserved for the research results. Key words: Market research, companies, business decisions, business.

A comparison of different solution approaches to the vehicle scheduling problem in a practical case

Dear SCPE Reader, We present a selection of papers which are extensions of papers presented at the 7-th International Symposium on Parallel and Distributed Computing, 1–5 July 2008, in Krakow, Poland. The motivation for publishing the selection in the SCPE Journal was, on the one hand, to present the flavour of the research reported at the conference and on the other hand to present some of the most relevant topics currently focused on the research on parallel and distributed computing in general. The selection contains only 6 papers out of about 60 presented at the conference, and thus, is far from covering all relevant topics represented at the ISPDC 2008. This is because not all of the invited authors were patient enough to accept a fairly long paper publishing process. Nevertheless, we hope that the presented papers will bring you closer to the research covered by the ISPDC conferences and will encourage you to participate in future ISPDC editions. The first paper ``The Impact of Workload Variability on Load Balancing Algorithms'' is by Marta Beltran and Antonio Guzman from King Juan Carlos University in Spain. It concerns an important topic of load balancing in cluster systems, namely adaptativity of the load balancing algorithms to changes of the workload in the system. Adequate accounting for additional load in the hosting system is of great relevance for correct optimization effects. The paper presents a thorough formal analysis of the workload variability metrics and their influence on the quality of load balancing algorithms. Four basic activities appearing in load balancing algorithms are identified, and based on them some algorithmic solutions are proposed to correctly deal with workload variability in system load balancing. The problem of dynamic load balancing algorithms robustness has been discussed. Two different robustness metrics sensitive to the applied type of opimization: local task-oriented or a global one enable selecting task remote execution or migration as load balancing operations. The proposed approach is illustrated with experiments. The second paper ``Model-Driven Engineering and Formal Validation of High-Performance Embedded Systems'' is by Abdoulaye Gamatie, Eric Rutten, Huafeng Yu, Pierre Boulet, Jean-Luc Dekeyser, from University of Lille and INRIA in France. The paper is concerned with a very advanced methodology of designing correct parallel embedded systems for intensive data-parallel computing. In their previous research, the authors of the paper designed the GASPARD embedded system design framework. It is based on the hardware/software co-design approach through model-driven engineering. The framework is based on an UML-like model specification language in which hardware and software elements are modelled using a component approach with special mechanisms for repetitive structures. This paper tries to combine the modelling framework of GASPARD with the mechanisms of synchronous languages to achieve design verifiability provided for such languages. The paper shows how GASPARD models can be translated into synchronous models based on data flow equations in order to formally check their correctness. The proposed approach is illustrated with an example of a video processing system. The third paper ``Relations Between Several Parallel Computational Models'' is by Stephan Bruda and Yuanqiao Zhang from Bishop’s University in Canada. The paper is concerned with theoretical aspects of shared memory systems described by the parallel random access machine PRAM model and aims in studying performance properties of different types of PRAM systems. The attention is focussed on analysing the computational power of two more sophisticated PRAM models (Combining CRCW and Broadcast Selective Reduction), which include data reduction in case of concurrent writes. The paper shows that these two models have equivalent computational power, which is a new result comparing the existing literature. The performance of both models applied to reconfigurable multiple bus machines was studied as a possible architectural solution for current VLSI processor implementations. It was shown that in such systems under reasonable assumptions concurrent-write does not enhance performance comparing the exclusive-write model. Another result important for the VLSI technology is that the Combining CRCW PRAM model (in which data of concurrent writes are arthmetically or logically combined before write) and the exclusive-write on directed reconfigurable busses perform in equivalent way under strong real-time requirements. The fourth paper ``Experiences with Mesh-Like Computations Using Prediction Binary Trees'' is by Gennaro Cordasco, Biagio Cosenza, Rosario de Chiara, Ugo Erra and Vittorio Scarano from the University ``degli Studi'' of Salerno and the University ``degli Studi della Biasilicata'' of Potenza in Italy. The paper concerns optimization methods for mesh-like computations in clusters of processors. The computations are perfomed assuming a phase-like program execution control using a tiling approach which reduces inter-processor communication. A temporal coherence is also assumed, which means that task sizes provide similar execution times in consecutive phases. Temporary coherent computations are structured in a Prediction Binary Tree, in which leaves represent computing tiles to be mapped to processors. A phase-by-phase semi-static load balancing is introduced to the scheduling algorithm. The scheduling algorithm is equipped with a predictor, which estimates the computation time of next phase tiles based on previous execution times and modifies the tiles to achieve balanced execution in phases. For this, two heuristics are used to leverage on data locality in processors. The proposed approach is illustrated by the example of interactive rendering with Parallel Ray Tracing algorithm. The fifth paper ``The Influence of the IBM pSeries Servers Virtualization Mechanism on Dynamic Resource Allocation in AIX 5L'' is by Maciej Mlynski from ASpartner Limited in Poland. The paper concerns a very up-to-date problem of system virtualization and presents the results of research carried on IBM pSeries servers. IBM is strongly developing the virtualization technique especially on IBM pSeries servers enabling an improved and flexible sharing of system resources between applications. The paper investigates novel facilities for dynamic resource management such as micro-partitioning and partition load manager. They enable dynamic creation of workload logical partitions of system resources and their dynamic mangement. It includes run-time resource re-alocation between logical partitions including setting of sharing specifications as well as run-time adding/removing/setting parameters of resources in the system. It remains an open question how to properly tune parameters of the operating system using the provided virtualization facilities to obtain the best efficiency for a given application program. The paper presents the results of experiments which study the effects of tuning the disk subsystem parameters under the IBM AIX 5L operating system with the use of the provided virtualization facilities on the resulting application execution performance. The results show that even small deterioration in the resource pool status requires an immediate adaptation of the operating system parameters to maintain the required performance. The sixth paper ``HeteroPBLAS: A Set of Parallel Basic Linear Algebra Subprograms Optimized for Heterogeneous Computational Clusters'' is by Ravi Reddy, Alexey Lastovetsky and Pedro Alonso from University College Dublin in Ireland and Polytechnic University of Valencia in Spain. The paper concerns the methodology for parallelization of linear algebra computations for execution in heterogeneous cluster environments. The design of the HeteroPBLAS library (Parallel Basic Linear Algebra Subprograms) for heterogeneous computational clusters is presented. The main contribution of the paper is the automation of the parallelization and optimization of the PBLAS, which is done by means of a special user interface and the underlying set of functions. An important element is here a performance model that is based on program code instrumentation, which determines parameters of the application and the executive heterogeneous platform relevant for execution performance of parallel code. The parameter values specified for or returned by execution of the performance model functions are next used for generation and optimal mapping of the parallel code of the library subroutines. The proposed approach is illustrated by experimental results of execution of optimized HeteroPBLAS programs on homogeneous and heterogeneous computing clusters. Marek Tudruj

All around the world, a large number of people rely on public transport. These days, most transport users automatically pay with a smart-card when using public transport systems. Due to people's frequent usage of public transport, researchers are invested in better understanding passengers' behaviour patterns. The smart-card system is an ideal source of data for researchers as it is capable of storing large amounts of data on transit users, and when used for a long time, can be the source needed for detailed investigation into passengers' trip patterns, both habitual and sporadic.There are two types of changes in the variation of passengers' movements. First, there exists a short-term pattern, which is expressed as a momentary variation in movement pattern. Second is more long-term and of specific interest to transport officials who are interested in understanding the underlying factors that may disturb the more regular and longer lasting habits. As such, the nature of this study is designed so as to improve detection and the analysis of temporal long-term changes in passengers' movement patterns by relying on the smart-card system in order to obtain detailed information about passengers, such as their time-of-day and day-of-week behaviour patterns.One of the main problems with using big data, however, is that the processing of it is time-inefficient and expensive when performed manually. The study therefore aims to process the smart-card data using an automated approach where the proposed framework relies on machine learning and pattern recognition techniques. This result strives to aid public transit operators to improve the provision of public transport to commuters by taking better account specific changes in passengers' movement behaviour. The research aims to provide public transit operators information that will serve to improve understanding of commuters' behaviours. As a result, public transit operators may better design customer retention strategies that will improve transit services and provide greater efficiency in inter-regional migration.

Since the Industrial Revolution, both manufacture and business industries have been utilizing the limited resources to reach the maximize value of economics, hence the equipment automations in the industries have been developed. In recent years, efficiency has become one of the key factors for enhancing a business’ competitiveness in domestic environment of the well developing manufacturing industry; how to reduce the time from receiving a order to delivery is especially important for the supplier of automation system. However, the tendency of mass customization and make to order has increased the level of difficulty for project scheduling; therefore, how to quickly and steadily provide the system with automation equipments for clients is the main goal for every automation system supplier. Theory Of Constraints is a thinking method used to develop a particular management technology, and this technique has been applied in many domains of management. Critical Chain Project Management (CCPM) is an application for the Theory Of Constraints, it is also one of the newly developed project managements. Therefore, this study applies both of these two management theory and method to discuss the problems occurs in project management processes of automation system and their solutions. This study is based on the perspective of automation system supplier and uses the concept of Theory Of Constraints and Critical Chain Project Management to resolve problems encountered during the process of project execution, as well to achieve the goal of work completion within the time schedule. It is also expected to develop a suitable management method for automation system to efficiently control each tasks in the project, to achieve the goal of optimal resource utilization, shorten the time of operation and easier to control project process during the execution phase.

Over the past years, Thai small and medium enterprises (SME) had to deal with changing economic situations and had to adapt to new technological evolutions, representing new challenges as well as new opportunities for doing business. With the forthcoming ASEAN Economic Community 2015, Thai SMEs will face an increase in competition and, as a possible solution, may have to adopt new information systems to remain competitive. The objectives of this study are (1) to identify the factors facilitating or hindering the adoption of cloud-based enterprise resource planning (ERP) systems by Thai SMEs and to (2) provide an analysis of the adoption and the implementation strategies. The research is based on a qualitative exploratory approach, relying on semistructured interviews with IT experts, IT managers and business owners to collect data, and on the template analysis method to analyze the data. Respondents have identified trust, cost control and the security of financial data as the most important factors for the adoption and selection of on-premise and cloud-based ERP systems. The adoption rate of cloud-based solutions appears to be low and local ERP providers face the challenge to discover the reasons why business owners do not adopt their solutions. First generation business owners prepare the transition to the next generation and want to better organize and structure how their businesses operates, but their own confidence in the technology still limit the adoption pace and the decision process. SMEs' strategies usually consist in a step-by-step implementation, consolidating the changes and readjusting the goals in case of setbacks, minimizing the consequences. ERP providers' strategies focus on new offerings with enhanced features and slowly integrate change management and extended support. Keywords: ERP, Cloud Computing, Small and Medium Enterprise (SME), Mobile App, Open Source, Organizational Innovation Adoption model.

Businesses and enterprises depend more than ever on IT service systems. Business processes are vulnerable to disruptions caused by failures in IT systems. Business Continuity Management addresses this problem and tries to identify and determine strategies and responses to overcome or mitigate possible business disruptions. In this paper we introduce a novel Business Continuity Model for IT systems and a Statistical Process Control based approach to perform an automated Business Impact Analysis.