The Maximally Diverse Grouping Problem is one of the well-known combinatorial optimization problems with applications in the assignment of students to groups or courses. Due to its NP-hardness several (meta)heuristic solution approaches have been presented in the literature. Most of them include...

The All-pairs shortest path problem (ALL-SPP) aims to find the shortest path joining all the vertices in a given graph. This study proposed a new optimal method, Dhouib-matrix-ALL-SPP (DM-ALL-SPP) to solve the ALL-SPP based on column-row navigation through the adjacency matrix. DM-ALL-SPP is...

The suitability of agents for tasks and ranked preference of tasks for agents play a significant role in problems where several agents are available to perform various tasks. The agents should be allocated to various tasks so that the corresponding assignment schedules must provide solution...

Selecting or adjusting attribute-levels (e.g. components, equipments, flavors, ingredients, prices, tastes) for multiple new and/or status quo products is an important task for a focal firm in a dynamic market. Usually, the goal is to maximize expected overall buyers' welfare based on consumers'...

We consider the block relocation problem (BRP), a combinatorial optimization problem that may arise in storage systems where items are organized in stacks. The objective is to retrieve all items in a predefined order with a minimal number of relocations. It can be distinguished between a...

Abstract Selecting or adjusting attribute-levels (e.g. components, equipments, flavors, ingredients, prices, tastes) for multiple new and/or status quo products is an important task for a focal firm in a dynamic market. Usually, the goal is to maximize expected overall buyers’ welfare based on...

Most metaheuristics lack a termination condition based on reasonable premises and guaranteeing the quality of the solution provided by the algorithm. We propose a methodological frame that distinguishes the concepts of properties of the final incumbent solution, rules and termination conditions....

This study proposes a novel and more efficient quantum algorithm for portfolio optimization using quantum combinatorial optimization (QCO) techniques. A recent construction developed in 2021 has sparked the field of financial portfolio optimization through the Quantum Walk Optimization Algorithm...