A study on multi-trip vehicle routing problem with time windows and meal break considerations

In the manpower scheduling problem with multiple trips vehicle routing and time windows consideration, a group of staff workers has to be assigned to a number of jobs in such a way that the total number of staff required is minimised, and each job’s requirements for manpower, transportation time, and time windows must be respected. Furthermore, if several staff is requested to cooperate, they must work on the job at the same time. The problem originates from manpower scheduling for the in-flight food loading operations and could be modeled as Multiple Trips Vehicle Routing and Scheduling Problem with Time Windows and meal break considerations (MTVRSPTW-MB). In this thesis, we present a mathematical model of MTVRSPTW-MB and show that even for a reduced problem; it is intractable on this small sample size of data. Therefore, we developed an original two-stage scheduling heuristic algorithm to cope with this complicated combinatorial optimisation problem. This heuristic uses some simple laxity scheduling and priority rules to do the job assignment and scheduling in two stages. The heuristic is tested on real-life problem instances supplied by one of the in-flight caterers from Malaysia. On top of that, a pre-processing data algorithm was developed to spread the demand as evenly as possible. We obtained excellent solutions in reduction manpower in all the cases within three seconds. We also evaluated the heuristic further by comparing it with a popular heuristic insertion algorithm. The computational results report the effectiveness and robustness of our proposed heuristics. Our heuristic algorithm has also proved computational bounded

Real-Life Optimum Shift Scheduling Design

In many industries, manpower shift scheduling poses problems that require immediate solutions. The fundamental need in this domain is to ensure that all shifts are assigned to cover all or as many jobs as possible. The shifts should additionally be planned with minimum manpower utilization, minimum manpower idleness and enhanced adaptability of employee schedules. The approach used in this study was to utilize an existing manpower prediction method to decide the minimum manpower required to complete all jobs. Based on the minimum manpower number and shift criteria, the shifts were assigned to form schedules using random pick and criteria-based selection methods. The potential schedules were then optimized and the best ones selected. Based on several realistic test instances, the proposed heuristic approach appears to offer promising solutions for shift scheduling as it improves shift idle time, complies with better shift starting time and significantly reduces the manpower needed and the time spent on creating schedules, regardless of data size

Real-Life Faculty Examination Timetabling to Utilise Room Used

Examination timetabling is an important and yet tedious task to do in every semester. The large number of courses and students increase the difficulty of developing a good examination timetable. Furthermore, the examination timeslots and rooms are very limited in this case study. Therefore, an improved version of two-stage heuristic is proposed and developed a web-based prototype (Faculty Examination Scheduling System, FESS 2.0) to solve faculty examination timetabling problem at Universiti Malaysia Sarawak (UNIMAS). The prototype has been practically used starting from Semester II, 2016/2017. The main objective of the proposed solution is to maximise the room utilisation and minimise the number of rooms for a splitting examination. The outcome of research not only outperform the previous prototype FESS 1.0 but also enhance the services given by faculty management

Heuristic method for optimum shift scheduling design

This paper describes a method to schedule shifts in the most optimum way desire for today’s cost sensitive industries.The main problem for this domain is to make sure all shifts are assigned to cover all or maximum jobs available.The shifts also need to be schedule with the least manpower possible, avoid manpower idling during the shift and take into consideration employee’s time adaptability.Our approach is to use the existing manpower prediction method to determine the minimum manpower require to complete all the jobs. Based on the minimum manpower number and shift criteria’s, the shifts are then assigned to form schedules using our proposed algorithm.The potential schedules are then optimized.Our prototype running data from airline staff shows that the method used can solve the problem efficiently even for large problem instances in seconds

Heuristic Algorithm for Multi-Location Lecture Timetabling

This paper studies a real faculty timetabling problem with multi-location consideration. Faculty of Cognitive Sciences and Human Development, UNIMAS offers a master's program by coursework to postgraduate students. The construction of timetables for all the courses offered is a tedious process due to constraints such as team-teaching allocation, unavailability dates of lecturers, and multi-location considerations. Therefore, a manually designed timetable is not as practical as it is time consuming when operational constraints must be fulfilled. In this paper, a two-stage heuristic algorithm is proposed to solve this postgraduate coursework timetable problem. This is because the heuristic algorithm is easy to apply and able to generate a feasible solution in a short time. The proposed two-stage heuristic algorithm consists of Lecturer Grouping Stage and Group Allocation Stage. In Stage I, the lecturers are assigned into four lecturer groups with the condition of no identical lecturers in each of the groups. Then, in Stage II, these groups are allocated into a set of academic weeks throughout the semester. The timeslot for each course can be allocated, and the team-teaching slot for the lecturers can be assigned in this stage. The result from the two-stage heuristic algorithm shows remarkable improvement over the real timetables solution by analyzing the distribution of lecture sessions of the courses

Real life working shift assignment problem

This study concerns about the working shift assignme\nt in an outlet of Supermarket X in Eastern Mall, Kuching. The working shift assignment needs to be solved at least once in every month. Current approval process of working shifts is too troublesome and time-consuming. Furthermore, the management staff cannot have an overview of manpower and working shift schedule. Thus, the aim of this study is to develop working shift assignment simulation and propose a working shift assignment solution. The main objective for this study is to fulfill manpower demand at minimum operation cost. Besides, the day off and meal break policy should be fulfilled accordingly. Demand based heuristic is proposed to assign working shift and the quality of the solution is evaluated by using the real data

PhishWHO: Phishing webpage detection via identity keywords extraction and target domain name finder

This paper proposes a phishing detection technique based on the difference between the target and actual identities of a webpage. The proposed phishing detection approach, called PhishWHO, can be divided into three phases. The first phase extracts identity keywords from the textual contents of the website, where a novel weighted URL tokens system based on the N-gram model is proposed. The second phase finds the target domain name by using a search engine, and the target domain name is selected based on identity-relevant features. In the final phase, a 3-tier identity matching system is proposed to determine the legitimacy of the query webpage. The overall experimental results suggest that the proposed system outperforms the conventional phishing detection methods considered

A Hybrid of Heuristic Orderings and Variable Neighbourhood Descent for a Real Life University Course Timetabling Problem

Academic institutions face timetabling problem every semester. Addressing timetabling problem at academic institutions is a challenging combinatorial optimisation task both in theory and practice. This is due to the size of the problem instances as well as the number of constraints that must be satisfied. Over the years, timetabling problem has attracted many researchers in proposing ways to find an optimal solution. In this paper, we investigate a hybrid of heuristic orderings and variable neighbourhood descent approach in tackling course timetabling problem at the Faculty of Computer Science and Information Technology (FCSIT), Universiti Malaysia Sarawak (UNIMAS). At FCSIT, some events of 4 lecture hours are not evenly spread over minimum working days and some events are conducted until 9 pm. The objectives of the study are to shorten the daily lecture hours and evenly distribute events’ lecture. In stage 1, heuristic orderings are utilised to find a feasible solution. In stage 2, a hybrid of heuristic orderings and variable neighbourhood descent approach are utilised to improve the quality of the solution. The proposed algorithm is tested on real-world data instances (semesters 1 and 2 of 2019/2020) of FCSIT, UNIMAS. Results show that certain heuristic ordering (largest degree or the combination of largest degree and largest enrolment) are better than others in generating a feasible solution. In addition, the number of timeslots required by heuristic ordering are less compared to that required by the existing timetabling software. In stage 2, the proposed algorithm manages to achieve soft constraint violations of 0 and 1 for instances for semesters 1 and 2, respectively. However, all HO manage to achieve 0 violation for both instances when the proposed algorithm is executed 30 times. Each neighbourhood structures defined in this study contributes to lowering the soft constraint violations thus ensuring a high-quality timetable. Results show that the order of neighbourhood structures do impact the number of soft constraint (SC1) violations achieved