Heuristic-Based Primer Set Minimization for PCR: Adaptation of Iterated Local Search for a Set Cover Variant

AmpliDiff is an algorithm for studying environmental samples. As the study of those DNA samples is complicated, the runtime of AmpliDiff holds back its usability. One time-consuming part is exactly solving a variant of the Set Cover problem. This paper researches whether this exact solution can be replaced by heuristics to reduce the runtime....

Exploring the Multi-Objective Dial-A-Ride Problem: An Analysis of Genetic Algorithms and MIP

The Multi-Objective Dial-a-Ride Problem (DARP) poses significant challenges in the field of transportation optimization, requiring the simultaneous optimization of conflicting objectives such as travel costs, emission, and customer ride times. In this research, we analyse two distinct approaches for tackling the Multi-Objective DARP: Mixed...

Reduce, Reuse, Recycle: On exploration of solution reuse in VRPTW

Solving routing problems efficiently is instrumental in minimizing operational costs in logistics. These routing problems are hard to solve and often take a lot of time to find a good solution. In this thesis, we present a methodology that tackles the challenge of efficiently solving recurring instances of the Vehicle Routing Problem with Time...

How can the behaviour of specialized heuristic solvers assist constraint solvers for optimization problems: A lookahead approach for Chuffed that emulates the behaviour of heuristic solvers

<br/>Constraint programming solvers provide a generalizable approach to finding solutions for optimization problems. However, when comparing the performance of constraint programming solvers to the performance of a heuristic solver for an optimization problem such as cluster editing, the heuristic solver is able to find near-optimal and optimal...

Combinatorial optimization for job sequencing with one common and multiple secondary resources by using a SAT solver augmented with a domain-specific heuristic

This paper solves job sequencing with one common and multiple secondary resources (JSOCMSR) problem by encoding it as a Boolean satisfiability (SAT) problem and applying domain-specific heuristics to improve the SAT solver’s performance. JSOCMSR problem is an NP-hard scheduling problem where each job utilizes two resources: a shared resource and...

Integration of variable selection heuristics into a MaxSAT solver for solving the multi-mode resource-constrained project scheduling problem

The multi-mode resource-constrained project scheduling problem (MRCPSP) is an extension of the resource-constrained project scheduling problem (RCPSP), which allows activities to be executed in multiple modes. The state-of-the-art solutions for solving this NP-Hard problem are dedicated algorithms and (meta-)heuristics. However, this paper...

Automatically designing diverse golf course routings

Designing golf course routings is a challenging problem as a golf course should obey the golf course regulation, be safe to play by having enough room between the holes and be diverse and challenging to the golf players. A potential exact solution can come in the form of a constraint programming model, in which solvers take care of the...

Resource-constraint project scheduling with task preemption and setup times by Boolean satisfiability encoding and satisfiability (SAT) solver

Scheduling has been subject to much research. The resource-constrained project scheduling problem (RCPSP) is no exception. With the multiple different variations and additions to the standard definition that are possible, many exact, heuristic and meta-heuristic approaches have been proposed. One of those variations is allowing tasks in the...

Finding Core-periphery Structure in Directed Networks: An Algorithm for Detecting Multiple-group Core-periphery Structure in Directed Netwoks

The core-periphery structure is a mesoscale topological structure that refers to the presence of a dense core and a sparse periphery. The core-periphery structure has been discovered in financial, biological, and technological networks. Various methods for detecting core-periphery structure have been proposed, exploring different discrete or...

An Evolutionary Algorithm for the Train Unit Shunting and Servicing Problem

The Train Unit Shunting and Servicing (TUSS) problem is an NP-hard problem encountered by the Dutch railway operator, Nederlandse Spoorwegen (NS). It considers trains at a shunting yard when they are not transporting passengers. It consists of four subproblems, involving assigning the trains at the yard to a transporting timetable (Matching),...

Deepification: Learning Variable Ordering Heuristics in Constraint Optimization Problems

Constraint programming is a paradigm for solving combinatorial problems by checking whether constraints are satisfied in a constraint satisfaction problem or by optimizing an objective in a constraint optimization problem. To find solutions, the solver needs to find a variable and value ordering. Numerous heuristics designed by human experts...

Optimization of the Locations of Virtual Network Functions

In traditional networks, the network functions are implemented as physical appliances which are called middleboxes and these middleboxes need to be deployed in predetermined locations throughout the network. Therefore one of the most important disadvantages of using middleboxes is that each network function deployment requires a great deal of...