Interactive approaches to the solution of a class of combinatorial problems

PhD ThesisThis thesis considers the usefulness of interaction between a human and a powerful computer in attempting to solve a class of discrete optimization problems. Some typical problems are described in chapters 1 and 2 and the effectiveness of their exact solution by existing methods is assessed. Chapter 3 presents some heuristic techniques which produce good approximate solutions and the value of such methods is discussed. An alternative approach, that of providing a mechanism for manmachine interaction is proposed in chapter 4. A system for providing easy access to a range of algorithmic and heuristic techniques is described. The system, named IMPACT, was implemented by the author and its many features include the interruption, interrogation, adjustment and resumption of a process or algorithm. Some novel interactive tree-manipulation techniques and their usage are introduced in chapter 5. This chapter also describes extensions to certain other heuristics in order to improve their power when used interactively. Throughout the thesis a job-shop scheduling problem serves as a useful vehicle for illustrating ideas. This problem was investigated extensively and chapter 6 is devoted to the topic. The idea of a critical path of jobs through machines is introduced together with the slack time of a job upon a machine under a particular schedule. Branch-and-bound approaches to the problem have been proposed in the past. The performance of such an approach has been substantially improved, as is shown by new results. The improvement stems from two sources both of which were discovered interactively; i) a different branching procedure designed to exploit features of the job-shop scheduling problem, and ii) more realistic lower bounds than those originally proposed. The final chapter discusses the generality of the approach and illustrates the extendability of IMPACT. Other discrete optimization problems are discussed briefly and a branch-andbound formulation to one of them, an assignment problem~ is presented. An interactive approach by other authors to the travelling salesman problem is reviewed and features similar to those experienced in the job-shop scheduling investigation are remarked upon. To conclude, the advantages to be gained from an interactive approach are discussed

The scheduling of manufacturing systems using Artificial Intelligence (AI) techniques in order to find optimal/near-optimal solutions.

This thesis aims to review and analyze the scheduling problem in general and Job Shop Scheduling Problem (JSSP) in particular and the solution techniques applied to these problems. The JSSP is the most general and popular hard combinational optimization problem in manufacturing systems. For the past sixty years, an enormous amount of research has been carried out to solve these problems. The literature review showed the inherent shortcomings of solutions to scheduling problems. This has directed researchers to develop hybrid approaches, as no single technique for scheduling has yet been successful in providing optimal solutions to these difficult problems, with much potential for improvements in the existing techniques. The hybrid approach complements and compensates for the limitations of each individual solution technique for better performance and improves results in solving both static and dynamic production scheduling environments. Over the past years, hybrid approaches have generally outperformed simple Genetic Algorithms (GAs). Therefore, two novel priority heuristic rules are developed: Index Based Heuristic and Hybrid Heuristic. These rules are applied to benchmark JSSP and compared with popular traditional rules. The results show that these new heuristic rules have outperformed the traditional heuristic rules over a wide range of benchmark JSSPs. Furthermore, a hybrid GA is developed as an alternate scheduling approach. The hybrid GA uses the novel heuristic rules in its key steps. The hybrid GA is applied to benchmark JSSPs. The hybrid GA is also tested on benchmark flow shop scheduling problems and industrial case studies. The hybrid GA successfully found solutions to JSSPs and is not problem dependent. The hybrid GA performance across the case studies has proved that the developed scheduling model can be applied to any real-world scheduling problem for achieving optimal or near-optimal solutions. This shows the effectiveness of the hybrid GA in real-world scheduling problems. In conclusion, all the research objectives are achieved. Finaly, the future work for the developed heuristic rules and the hybrid GA are discussed and recommendations are made on the basis of the results.Board of Trustees, Endowment Fund Project, KPK University of Engineering and Technology (UET), Peshawar and Higher Education Commission (HEC), Pakista

Sheet-Metal Production Scheduling Using AlphaGo Zero

This work investigates the applicability of a reinforcement learning (RL) approach, specifically AlphaGo Zero (AZ), for optimizing sheet-metal (SM) production schedules with respect to tardiness and material waste. SM production scheduling is a complex job shop scheduling problem (JSSP) with dynamic operation times, routing flexibility and supplementary constraints. SM production systems are capable of processing a large number of highly heterogeneous jobs simultaneously. While very large relative to the JSSP literature, the SM-JSSP instances investigated in this work are small relative to the SM production reality. Given the high dimensionality of the SM-JSSP, computation of an optimal schedule is not tractable. Simple heuristic solutions often deliver bad results. We use AZ to selectively search the solution space. To this end, a single player AZ version is pretrained using supervised learning on schedules generated by a heuristic, fine-tuned using RL and evaluated through comparison with a heuristic baseline and Monte Carlo Tree Search. It will be shown that AZ outperforms the other approaches. The work’s scientific contribution is twofold: On the one hand, a novel scheduling problem is formalized such that it can be tackled using RL approaches. On the other hand, it is proved that AZ can be successfully modified to provide a solution for the problem at hand, whereby a new line of research into real-world applications of AZ is opened

Moderating effects of cross-cultural dimensions on the relationship between persuasive smartphone application's design and acceptance-loyalty

Applying persuasive system design to different cultures has been a focus of many researchers as the global medium of communication has been centered within Smartphone via applications (apps). This is due to the vast proliferation of the Smartphone and the personal attachment of users to this device in various cultures. This led designers to search for ultimate ways to target users in specific regions of the world. The basic purpose of this study was to determine the relevance of cross-cultural factors to persuasive technologies, and the acceptance and loyalty of Smartphone apps. This was achieved by examining the moderating effects of Hofstede’s six cross-cultural dimensions on the relationship between Oinas-Kukkonen and Harjumaa’s Persuasive System Design (PSD), and acceptance and loyalty. By evaluating elements of persuasive systems design and cross-cultural dimensions, from user’s perspective, against a globally popular application like WhatsApp, an instrument was devised to investigate the cross-cultural adoption and continued use of Smartphone apps. Using this instrument, surveys were conducted for this research study to identify the influencing factors that have motivated the users from Malaysia, Netherlands, Germany, and the Kingdom of Saudi Arabia to adopt and continue using this application on a daily basis. These surveys, which included responses from 488 participants, further investigated if there is one cross-cultural dimension that has more moderating effects per country. The findings indicate an agreement among WhatsApp users from all four countries about their reasons for adopting and using this app, namely: social influence (93.7 percent), reliability (83.4 percent), dialog-support via feedback (76.4 percent), ease of use (90.5 percent) and small cost (87.7 percent). The results put new perspective that the gap among cultures is narrowing. Persuasive design strategies are particularly relevant to cultures across the globe. This study can aid the research community in investing efforts into enhancing the persuasive design framework for Smartphone apps

Survival and disinfection of SARS-Cov-2 in environment and contaminated surface

The detection of SARS-Cov-2 in the sewage and water resources has increased the awareness among the people about the possibility survival of SARS-Cov-2 in the environment and the potential to transmit into the human through food chain or water resources. Moreover, the surface contaminated by the virus need to be disinfected frequently by using an effective disinfectant, the current chapter discussed the efficiency of the most traditional treatment process of the sewage and wastewater, and their role in the elimination of the virus as well as the sterility assurance level concept. Moreover, the chemical disinfectant used currently and their temporary efficiency has been reviewed

Abandoned project restoration model (APRM) for residential construction projects

Incompletion of construction projects is a common phenomenon in Malaysia. Project abandonment has given an adverse consequences to the economy, society and environment. In the best interest of the end users and other parties involved in the contract, the best resolution for this abandoned projects is to successfully revive them, which has its’ stages and barriers along the way as well. The main aim of this research is to develop an effective model as a guide towards project restoration which could be used to mitigate the issue of abandoned residential construction projects in Malaysia. Identifying the factors contributing towards the restoration of the abandoned projects are important to have a successful completed project. This research was conducted in the purpose of identifying those significant factors in order to obtain the restoration process for abandoned projects where lastly the Abandoned Project Restoration Model (APRM) was developed. The research focuses on residential construction projects. This research comprises of both quantitative and qualitative approaches and process, where a pilot survey and full survey, and as well as interview analysis were conducted. Factor model was developed using AMOS and lastly the developed model was validated and tested by related officials. The outcome of this research showed that the most significant factor for abandoned project restoration is Management Aspects. A complete restoration process based on the significant factors identified were also obtained. This model is seen as useful in contributing and as well as assisting the restoration of the abandoned projects in Malaysia and could be used as a guideline for that purpose

Welcome to OR&S! Where students, academics and professionals come together

In this manuscript, an overview is given of the activities done at the Operations Research and Scheduling (OR&S) research group of the faculty of Economics and Business Administration of Ghent University. Unlike the book published by [1] that gives a summary of all academic and professional activities done in the field of Project Management in collaboration with the OR&S group, the focus of the current manuscript lies on academic publications and the integration of these published results in teaching activities. An overview is given of the publications from the very beginning till today, and some of the topics that have led to publications are discussed in somewhat more detail. Moreover, it is shown how the research results have been used in the classroom to actively involve students in our research activities

A hybrid shifting bottleneck-tabu search heuristic for the job shop total weighted tardiness problem

In this paper, we study the job shop scheduling problem with the objective of minimizing the total weighted tardiness. We propose a hybrid shifting bottleneck - tabu search (SB-TS) algorithm by replacing the reoptimization step in the shifting bottleneck (SB) algorithm by a tabu search (TS). In terms of the shifting bottleneck heuristic, the proposed tabu search optimizes the total weighted tardiness for partial schedules in which some machines are currently assumed to have infinite capacity. In the context of tabu search, the shifting bottleneck heuristic features a long-term memory which helps to diversify the local search. We exploit this synergy to develop a state-of-the-art algorithm for the job shop total weighted tardiness problem (JS-TWT). The computational effectiveness of the algorithm is demonstrated on standard benchmark instances from the literature

Heuristics for the distributed blocking Ffow shop scheduling problem

Postprint (published version