Bounded and Unbounded Verification Using Hardware and Software Verifiers

Artifact for POPL paper Foundations for Natural Proofs and Quantifier Instantiation

Repo for Noisebox 2018 version (now officially v3)

LIA (sat)

python27

Benchmarks from the CHC-COMP 2019

Abstracted Boolector

Allows user to input a partially filled sudoku grid and outputs a complete sudoku grid with those squares. I use an SMT solver to find the solution.

Recommendation Engine Module

6800 CPU implemented in nmigen

My experiments with SymbiYosys

Software and CAD models of the footband FEEDI providing navigation information via haptic feedback

creating file to solve Killer Sudoku with Z3 Theorem Prover

Examples to test sequence theory in cvc4

SMTLIB syntax highlighting for Sublime Text 3

It has become very common nowadays, especially after the outbreak of the COVID-19 pandemic, to send or receive items online (food, goods, clothes, documents, . . . ). Hence, it is more and more important for companies to efficiently schedule the dispatching of items through different couriers, in order to minimize the transportation costs. As the combinatorial decision and optimization expert, the student is assigned to solve the Multiple Couriers Planning (MCP) problem which is defined as follows. We have m couriers that must distribute n ≥ m items at different customer locations. Each courier i has a maximum load size li. Each item j has a distribution point dj and a size sj (which can represent for instance a weight or a volume). The goal of MCP is to decide for each courier the items to be distributed and plan a tour (i.e. a sequence of location points to visit) to perform the necessary distribution tasks. Each courier tour must start and end at a given origin point o. Moreover, the maximum load li of the courier i should be respected when items are assigned to it. The objective is to minimize the total tour distance.